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<li><a class="reference internal" href="#illustration-of-pipeline-and-gridsearchcv">Illustration of <code class="docutils literal"><span class="pre">Pipeline</span></code> and <code class="docutils literal"><span class="pre">GridSearchCV</span></code></a></li>
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<div class="section" id="selecting-dimensionality-reduction-with-pipeline-and-gridsearchcv">
<span id="sphx-glr-auto-examples-plot-compare-reduction-py"></span><h1>Selecting dimensionality reduction with Pipeline and GridSearchCV<a class="headerlink" href="#selecting-dimensionality-reduction-with-pipeline-and-gridsearchcv" title="Permalink to this headline">¶</a></h1>
<p>This example constructs a pipeline that does dimensionality
reduction followed by prediction with a support vector
classifier. It demonstrates the use of <code class="docutils literal"><span class="pre">GridSearchCV</span></code> and
<code class="docutils literal"><span class="pre">Pipeline</span></code> to optimize over different classes of estimators in a
single CV run – unsupervised <code class="docutils literal"><span class="pre">PCA</span></code> and <code class="docutils literal"><span class="pre">NMF</span></code> dimensionality
reductions are compared to univariate feature selection during
the grid search.</p>
<p>Additionally, <code class="docutils literal"><span class="pre">Pipeline</span></code> can be instantiated with the <code class="docutils literal"><span class="pre">memory</span></code>
argument to memoize the transformers within the pipeline, avoiding to fit
again the same transformers over and over.</p>
<p>Note that the use of <code class="docutils literal"><span class="pre">memory</span></code> to enable caching becomes interesting when the
fitting of a transformer is costly.</p>
<div class="section" id="illustration-of-pipeline-and-gridsearchcv">
<h2>Illustration of <code class="docutils literal"><span class="pre">Pipeline</span></code> and <code class="docutils literal"><span class="pre">GridSearchCV</span></code><a class="headerlink" href="#illustration-of-pipeline-and-gridsearchcv" title="Permalink to this headline">¶</a></h2>
<blockquote>
<div>This section illustrates the use of a <code class="docutils literal"><span class="pre">Pipeline</span></code> with
<code class="docutils literal"><span class="pre">GridSearchCV</span></code></div></blockquote>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="c1"># Authors: Robert McGibbon, Joel Nothman, Guillaume Lemaitre</span>
<span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">print_function</span><span class="p">,</span> <span class="n">division</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits" title="View documentation for sklearn.datasets.load_digits"><span class="n">load_digits</span></a>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV" title="View documentation for sklearn.model_selection.GridSearchCV"><span class="n">GridSearchCV</span></a>
<span class="kn">from</span> <span class="nn">sklearn.pipeline</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.pipeline.Pipeline.html#sklearn.pipeline.Pipeline" title="View documentation for sklearn.pipeline.Pipeline"><span class="n">Pipeline</span></a>
<span class="kn">from</span> <span class="nn">sklearn.svm</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.svm.LinearSVC.html#sklearn.svm.LinearSVC" title="View documentation for sklearn.svm.LinearSVC"><span class="n">LinearSVC</span></a>
<span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">,</span> <a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a>
<span class="kn">from</span> <span class="nn">sklearn.feature_selection</span> <span class="kn">import</span> <a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">,</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a>
<span class="k">print</span><span class="p">(</span><span class="vm">__doc__</span><span class="p">)</span>
<span class="n">pipe</span> <span class="o">=</span> <a href="../modules/generated/sklearn.pipeline.Pipeline.html#sklearn.pipeline.Pipeline" title="View documentation for sklearn.pipeline.Pipeline"><span class="n">Pipeline</span></a><span class="p">([</span>
<span class="p">(</span><span class="s1">'reduce_dim'</span><span class="p">,</span> <a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">()),</span>
<span class="p">(</span><span class="s1">'classify'</span><span class="p">,</span> <a href="../modules/generated/sklearn.svm.LinearSVC.html#sklearn.svm.LinearSVC" title="View documentation for sklearn.svm.LinearSVC"><span class="n">LinearSVC</span></a><span class="p">())</span>
<span class="p">])</span>
<span class="n">N_FEATURES_OPTIONS</span> <span class="o">=</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">8</span><span class="p">]</span>
<span class="n">C_OPTIONS</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">1000</span><span class="p">]</span>
<span class="n">param_grid</span> <span class="o">=</span> <span class="p">[</span>
<span class="p">{</span>
<span class="s1">'reduce_dim'</span><span class="p">:</span> <span class="p">[</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">),</span> <a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">()],</span>
<span class="s1">'reduce_dim__n_components'</span><span class="p">:</span> <span class="n">N_FEATURES_OPTIONS</span><span class="p">,</span>
<span class="s1">'classify__C'</span><span class="p">:</span> <span class="n">C_OPTIONS</span>
<span class="p">},</span>
<span class="p">{</span>
<span class="s1">'reduce_dim'</span><span class="p">:</span> <span class="p">[</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a><span class="p">)],</span>
<span class="s1">'reduce_dim__k'</span><span class="p">:</span> <span class="n">N_FEATURES_OPTIONS</span><span class="p">,</span>
<span class="s1">'classify__C'</span><span class="p">:</span> <span class="n">C_OPTIONS</span>
<span class="p">},</span>
<span class="p">]</span>
<span class="n">reducer_labels</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'PCA'</span><span class="p">,</span> <span class="s1">'NMF'</span><span class="p">,</span> <span class="s1">'KBest(chi2)'</span><span class="p">]</span>
<span class="n">grid</span> <span class="o">=</span> <a href="../modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV" title="View documentation for sklearn.model_selection.GridSearchCV"><span class="n">GridSearchCV</span></a><span class="p">(</span><span class="n">pipe</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="n">param_grid</span><span class="p">)</span>
<span class="n">digits</span> <span class="o">=</span> <a href="../modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits" title="View documentation for sklearn.datasets.load_digits"><span class="n">load_digits</span></a><span class="p">()</span>
<span class="n">grid</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">digits</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="n">digits</span><span class="o">.</span><span class="n">target</span><span class="p">)</span>
<span class="n">mean_scores</span> <span class="o">=</span> <a href="http://docs.scipy.org/doc/numpy-1.8.1/reference/generated/numpy.array.html#numpy.array" title="View documentation for numpy.array"><span class="n">np</span><span class="o">.</span><span class="n">array</span></a><span class="p">(</span><span class="n">grid</span><span class="o">.</span><span class="n">cv_results_</span><span class="p">[</span><span class="s1">'mean_test_score'</span><span class="p">])</span>
<span class="c1"># scores are in the order of param_grid iteration, which is alphabetical</span>
<span class="n">mean_scores</span> <span class="o">=</span> <span class="n">mean_scores</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">C_OPTIONS</span><span class="p">),</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">N_FEATURES_OPTIONS</span><span class="p">))</span>
<span class="c1"># select score for best C</span>
<span class="n">mean_scores</span> <span class="o">=</span> <span class="n">mean_scores</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">bar_offsets</span> <span class="o">=</span> <span class="p">(</span><a href="http://docs.scipy.org/doc/numpy-1.8.1/reference/generated/numpy.arange.html#numpy.arange" title="View documentation for numpy.arange"><span class="n">np</span><span class="o">.</span><span class="n">arange</span></a><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">N_FEATURES_OPTIONS</span><span class="p">))</span> <span class="o">*</span>
<span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">reducer_labels</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="o">+</span> <span class="o">.</span><span class="mi">5</span><span class="p">)</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.figure.AxesStack.html#matplotlib.figure" title="View documentation for matplotlib.pyplot.figure"><span class="n">plt</span><span class="o">.</span><span class="n">figure</span></a><span class="p">()</span>
<span class="n">COLORS</span> <span class="o">=</span> <span class="s1">'bgrcmyk'</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="n">reducer_scores</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">reducer_labels</span><span class="p">,</span> <span class="n">mean_scores</span><span class="p">)):</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.bar.html#matplotlib.pyplot.bar" title="View documentation for matplotlib.pyplot.bar"><span class="n">plt</span><span class="o">.</span><span class="n">bar</span></a><span class="p">(</span><span class="n">bar_offsets</span> <span class="o">+</span> <span class="n">i</span><span class="p">,</span> <span class="n">reducer_scores</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">COLORS</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title" title="View documentation for matplotlib.pyplot.title"><span class="n">plt</span><span class="o">.</span><span class="n">title</span></a><span class="p">(</span><span class="s2">"Comparing feature reduction techniques"</span><span class="p">)</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.xlabel" title="View documentation for matplotlib.pyplot.xlabel"><span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span></a><span class="p">(</span><span class="s1">'Reduced number of features'</span><span class="p">)</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.xticks.html#matplotlib.pyplot.xticks" title="View documentation for matplotlib.pyplot.xticks"><span class="n">plt</span><span class="o">.</span><span class="n">xticks</span></a><span class="p">(</span><span class="n">bar_offsets</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">reducer_labels</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span><span class="p">,</span> <span class="n">N_FEATURES_OPTIONS</span><span class="p">)</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.ylabel.html#matplotlib.pyplot.ylabel" title="View documentation for matplotlib.pyplot.ylabel"><span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span></a><span class="p">(</span><span class="s1">'Digit classification accuracy'</span><span class="p">)</span>
<a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.ylim.html#matplotlib.pyplot.ylim" title="View documentation for matplotlib.pyplot.ylim"><span class="n">plt</span><span class="o">.</span><span class="n">ylim</span></a><span class="p">((</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
<a href="http://matplotlib.org/api/legend_api.html#matplotlib.legend" title="View documentation for matplotlib.pyplot.legend"><span class="n">plt</span><span class="o">.</span><span class="n">legend</span></a><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">'upper left'</span><span class="p">)</span>
</pre></div>
</div>
<img alt="../_images/sphx_glr_plot_compare_reduction_001.png" class="align-center" src="../_images/sphx_glr_plot_compare_reduction_001.png" />
</div>
<div class="section" id="caching-transformers-within-a-pipeline">
<h2>Caching transformers within a <code class="docutils literal"><span class="pre">Pipeline</span></code><a class="headerlink" href="#caching-transformers-within-a-pipeline" title="Permalink to this headline">¶</a></h2>
<blockquote>
<div><p>It is sometimes worthwhile storing the state of a specific transformer
since it could be used again. Using a pipeline in <code class="docutils literal"><span class="pre">GridSearchCV</span></code> triggers
such situations. Therefore, we use the argument <code class="docutils literal"><span class="pre">memory</span></code> to enable caching.</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">Note that this example is, however, only an illustration since for this
specific case fitting PCA is not necessarily slower than loading the
cache. Hence, use the <code class="docutils literal"><span class="pre">memory</span></code> constructor parameter when the fitting
of a transformer is costly.</p>
</div>
</div></blockquote>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">tempfile</span> <span class="kn">import</span> <span class="n">mkdtemp</span>
<span class="kn">from</span> <span class="nn">shutil</span> <span class="kn">import</span> <span class="n">rmtree</span>
<span class="kn">from</span> <span class="nn">sklearn.externals.joblib</span> <span class="kn">import</span> <span class="n">Memory</span>
<span class="c1"># Create a temporary folder to store the transformers of the pipeline</span>
<span class="n">cachedir</span> <span class="o">=</span> <span class="n">mkdtemp</span><span class="p">()</span>
<span class="n">memory</span> <span class="o">=</span> <span class="n">Memory</span><span class="p">(</span><span class="n">cachedir</span><span class="o">=</span><span class="n">cachedir</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">cached_pipe</span> <span class="o">=</span> <a href="../modules/generated/sklearn.pipeline.Pipeline.html#sklearn.pipeline.Pipeline" title="View documentation for sklearn.pipeline.Pipeline"><span class="n">Pipeline</span></a><span class="p">([(</span><span class="s1">'reduce_dim'</span><span class="p">,</span> <a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">()),</span>
<span class="p">(</span><span class="s1">'classify'</span><span class="p">,</span> <a href="../modules/generated/sklearn.svm.LinearSVC.html#sklearn.svm.LinearSVC" title="View documentation for sklearn.svm.LinearSVC"><span class="n">LinearSVC</span></a><span class="p">())],</span>
<span class="n">memory</span><span class="o">=</span><span class="n">memory</span><span class="p">)</span>
<span class="c1"># This time, a cached pipeline will be used within the grid search</span>
<span class="n">grid</span> <span class="o">=</span> <a href="../modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV" title="View documentation for sklearn.model_selection.GridSearchCV"><span class="n">GridSearchCV</span></a><span class="p">(</span><span class="n">cached_pipe</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">param_grid</span><span class="o">=</span><span class="n">param_grid</span><span class="p">)</span>
<span class="n">digits</span> <span class="o">=</span> <a href="../modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits" title="View documentation for sklearn.datasets.load_digits"><span class="n">load_digits</span></a><span class="p">()</span>
<span class="n">grid</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">digits</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="n">digits</span><span class="o">.</span><span class="n">target</span><span class="p">)</span>
<span class="c1"># Delete the temporary cache before exiting</span>
<span class="n">rmtree</span><span class="p">(</span><span class="n">cachedir</span><span class="p">)</span>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-default"><div class="highlight"><pre><span></span><span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.PCA.html#sklearn.decomposition.PCA" title="View documentation for sklearn.decomposition.PCA"><span class="n">PCA</span></a><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">iterated_power</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">svd_solver</span><span class="o">=</span><span class="s1">'auto'</span><span class="p">,</span> <span class="n">tol</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">whiten</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.2</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.1</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">6</span><span class="n">c9faf767180734537ee1460d687aa7e</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fcd112fbe1836f85a32975165f6137db</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">571</span><span class="n">f5a1ed076993db04791fc833234d1</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ae28f7e0b3597cf142e9d86a07e61d94</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ff1dd0fc986140704ba90a99d238ff4c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">5</span><span class="n">da0220bd504aa094c1184a66c83da04</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">586840</span><span class="n">f33912a6396ecdf756b2392e5c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">d366660351b7d8ae30f884c98b91a404</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">7</span><span class="n">aaf51de31c01b79de9d29cb573cb570</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mf">4e5019335626</span><span class="n">f2a34b72f19ef3a94309</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">dc6c0877e1e3599d87ca0f9083fc3cd</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">2763795884</span><span class="n">a037217f3b847e4d273878</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">77092</span><span class="n">ef32d818647bde9f3c80442a311</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fad793302163ebf78158c2663bdee8a6</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">641667166004</span><span class="n">b7daf56bb2e1d7d07897</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">bdacb7a1fdfec97d03052b520a53fda</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">72</span><span class="n">aa21c9e89f9c39cdde34a6eb18c4a5</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">33</span><span class="n">b991b23bfb8a4517dd51f338152ad9</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">6</span><span class="n">c9faf767180734537ee1460d687aa7e</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fcd112fbe1836f85a32975165f6137db</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">571</span><span class="n">f5a1ed076993db04791fc833234d1</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ae28f7e0b3597cf142e9d86a07e61d94</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ff1dd0fc986140704ba90a99d238ff4c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">5</span><span class="n">da0220bd504aa094c1184a66c83da04</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">586840</span><span class="n">f33912a6396ecdf756b2392e5c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">d366660351b7d8ae30f884c98b91a404</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">7</span><span class="n">aaf51de31c01b79de9d29cb573cb570</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mf">4e5019335626</span><span class="n">f2a34b72f19ef3a94309</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">dc6c0877e1e3599d87ca0f9083fc3cd</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">2763795884</span><span class="n">a037217f3b847e4d273878</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">77092</span><span class="n">ef32d818647bde9f3c80442a311</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fad793302163ebf78158c2663bdee8a6</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">641667166004</span><span class="n">b7daf56bb2e1d7d07897</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">bdacb7a1fdfec97d03052b520a53fda</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">72</span><span class="n">aa21c9e89f9c39cdde34a6eb18c4a5</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">33</span><span class="n">b991b23bfb8a4517dd51f338152ad9</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">6</span><span class="n">c9faf767180734537ee1460d687aa7e</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fcd112fbe1836f85a32975165f6137db</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">571</span><span class="n">f5a1ed076993db04791fc833234d1</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ae28f7e0b3597cf142e9d86a07e61d94</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">ff1dd0fc986140704ba90a99d238ff4c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">5</span><span class="n">da0220bd504aa094c1184a66c83da04</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">586840</span><span class="n">f33912a6396ecdf756b2392e5c</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">d366660351b7d8ae30f884c98b91a404</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">7</span><span class="n">aaf51de31c01b79de9d29cb573cb570</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mf">4e5019335626</span><span class="n">f2a34b72f19ef3a94309</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">dc6c0877e1e3599d87ca0f9083fc3cd</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">2763795884</span><span class="n">a037217f3b847e4d273878</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">77092</span><span class="n">ef32d818647bde9f3c80442a311</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fad793302163ebf78158c2663bdee8a6</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">641667166004</span><span class="n">b7daf56bb2e1d7d07897</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">bdacb7a1fdfec97d03052b520a53fda</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">72</span><span class="n">aa21c9e89f9c39cdde34a6eb18c4a5</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">33</span><span class="n">b991b23bfb8a4517dd51f338152ad9</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.feature_selection.SelectKBest.html#sklearn.feature_selection.SelectKBest" title="View documentation for sklearn.feature_selection.SelectKBest"><span class="n">SelectKBest</span></a><span class="p">(</span><span class="n">k</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">score_func</span><span class="o">=<</span><span class="n">function</span> <a href="../modules/generated/sklearn.feature_selection.chi2.html#sklearn.feature_selection.chi2" title="View documentation for sklearn.feature_selection.chi2"><span class="n">chi2</span></a> <span class="n">at</span> <span class="mh">0x2b60c0903048</span><span class="o">></span><span class="p">),</span> <span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">4</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">c50184f7388eac6bdf390382f6148ab</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">b03168ef893036c56cec0c61e0f19053</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">c428c47ad448999e93928024d512bb0</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">78</span><span class="n">cb432d6f087bf113dcf0b85abfe254</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">8</span><span class="n">de24a51226ce233d56b097ca8580a8b</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">b9959b87f4003912026684a1f5d467d</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fe2eddfc8beaf1174496078d2d423341</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">61</span><span class="n">bdce54b69043ef8c334ba66b85fd83</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">9</span><span class="n">fc00199cd62065fceaf38d2908d7811</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">c50184f7388eac6bdf390382f6148ab</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">b03168ef893036c56cec0c61e0f19053</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">c428c47ad448999e93928024d512bb0</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">78</span><span class="n">cb432d6f087bf113dcf0b85abfe254</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">8</span><span class="n">de24a51226ce233d56b097ca8580a8b</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">b9959b87f4003912026684a1f5d467d</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">fe2eddfc8beaf1174496078d2d423341</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">61</span><span class="n">bdce54b69043ef8c334ba66b85fd83</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">9</span><span class="n">fc00199cd62065fceaf38d2908d7811</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">c50184f7388eac6bdf390382f6148ab</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="n">b03168ef893036c56cec0c61e0f19053</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">3</span><span class="n">c428c47ad448999e93928024d512bb0</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">78</span><span class="n">cb432d6f087bf113dcf0b85abfe254</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">8</span><span class="n">de24a51226ce233d56b097ca8580a8b</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">0</span><span class="n">b9959b87f4003912026684a1f5d467d</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
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<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">61</span><span class="n">bdce54b69043ef8c334ba66b85fd83</span>
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<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span><span class="p">:</span> <span class="n">Loading</span> <span class="n">_fit_transform_one</span> <span class="kn">from</span> <span class="o">/</span><span class="n">tmp</span><span class="o">/</span><span class="n">tmp7alkiyzr</span><span class="o">/</span><span class="n">joblib</span><span class="o">/</span><span class="n">sklearn</span><span class="o">/</span><span class="n">pipeline</span><span class="o">/</span><span class="n">_fit_transform_one</span><span class="o">/</span><span class="mi">9</span><span class="n">fc00199cd62065fceaf38d2908d7811</span>
<span class="n">___________________________________fit_transform_one</span> <span class="n">cache</span> <span class="n">loaded</span> <span class="o">-</span> <span class="mf">0.0</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
<span class="n">________________________________________________________________________________</span>
<span class="p">[</span><span class="n">Memory</span><span class="p">]</span> <span class="n">Calling</span> <span class="n">sklearn</span><span class="o">.</span><span class="n">pipeline</span><span class="o">.</span><span class="n">_fit_transform_one</span><span class="o">...</span>
<span class="n">_fit_transform_one</span><span class="p">(</span><a href="../modules/generated/sklearn.decomposition.NMF.html#sklearn.decomposition.NMF" title="View documentation for sklearn.decomposition.NMF"><span class="n">NMF</span></a><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">beta_loss</span><span class="o">=</span><span class="s1">'frobenius'</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">max_iter</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="n">n_components</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s1">'cd'</span><span class="p">,</span>
<span class="n">tol</span><span class="o">=</span><span class="mf">0.0001</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="kc">None</span><span class="p">,</span> <span class="n">array</span><span class="p">([[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">],</span>
<span class="o">...</span><span class="p">,</span>
<span class="p">[</span><span class="mf">0.</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mf">0.</span><span class="p">]]),</span> <span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="o">...</span><span class="p">,</span> <span class="mi">8</span><span class="p">]))</span>
<span class="n">________________________________________________fit_transform_one</span> <span class="o">-</span> <span class="mf">0.2</span><span class="n">s</span><span class="p">,</span> <span class="mf">0.0</span><span class="nb">min</span>
</pre></div>
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<p>The <code class="docutils literal"><span class="pre">PCA</span></code> fitting is only computed at the evaluation of the first
configuration of the <code class="docutils literal"><span class="pre">C</span></code> parameter of the <code class="docutils literal"><span class="pre">LinearSVC</span></code> classifier. The
other configurations of <code class="docutils literal"><span class="pre">C</span></code> will trigger the loading of the cached <code class="docutils literal"><span class="pre">PCA</span></code>
estimator data, leading to save processing time. Therefore, the use of
caching the pipeline using <code class="docutils literal"><span class="pre">memory</span></code> is highly beneficial when fitting
a transformer is costly.</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><a href="http://matplotlib.org/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="View documentation for matplotlib.pyplot.show"><span class="n">plt</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
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