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<p class="first admonition-title">Note</p>
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<div class="sphx-glr-example-title section" id="lasso-path-using-lars">
<span id="sphx-glr-auto-examples-linear-model-plot-lasso-lars-py"></span><h1>Lasso path using LARS<a class="headerlink" href="#lasso-path-using-lars" title="Permalink to this headline">¶</a></h1>
<p>Computes Lasso Path along the regularization parameter using the LARS
algorithm on the diabetes dataset. Each color represents a different
feature of the coefficient vector, and this is displayed as a function
of the regularization parameter.</p>
<img alt="../../_images/sphx_glr_plot_lasso_lars_001.png" class="sphx-glr-single-img" src="../../_images/sphx_glr_plot_lasso_lars_001.png" />
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none"><div class="highlight"><pre><span></span>Computing regularization path using the LARS ...
.
</pre></div>
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<div class="line-block">
<div class="line"><br /></div>
</div>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="vm">__doc__</span><span class="p">)</span>
<span class="c1"># Author: Fabian Pedregosa <[email protected]></span>
<span class="c1"># Alexandre Gramfort <[email protected]></span>
<span class="c1"># License: BSD 3 clause</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">linear_model</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="n">diabetes</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.datasets.load_diabetes.html#sklearn.datasets.load_diabetes" title="View documentation for sklearn.datasets.load_diabetes"><span class="n">datasets</span><span class="o">.</span><span class="n">load_diabetes</span></a><span class="p">()</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">diabetes</span><span class="o">.</span><span class="n">data</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">diabetes</span><span class="o">.</span><span class="n">target</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"Computing regularization path using the LARS ..."</span><span class="p">)</span>
<span class="n">_</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">coefs</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.linear_model.lars_path.html#sklearn.linear_model.lars_path" title="View documentation for sklearn.linear_model.lars_path"><span class="n">linear_model</span><span class="o">.</span><span class="n">lars_path</span></a><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'lasso'</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">xx</span> <span class="o">=</span> <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html#numpy.sum" title="View documentation for numpy.sum"><span class="n">np</span><span class="o">.</span><span class="n">sum</span></a><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">coefs</span><span class="o">.</span><span class="n">T</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">xx</span> <span class="o">/=</span> <span class="n">xx</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
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<span class="n">ymin</span><span class="p">,</span> <span class="n">ymax</span> <span class="o">=</span> <a href="https://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>
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<a href="https://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">'Coefficients'</span><span class="p">)</span>
<a href="https://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="s1">'LASSO Path'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.axis.html#matplotlib.pyplot.axis" title="View documentation for matplotlib.pyplot.axis"><span class="n">plt</span><span class="o">.</span><span class="n">axis</span></a><span class="p">(</span><span class="s1">'tight'</span><span class="p">)</span>
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