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<li><a class="reference internal" href="#">Plot individual and voting regression predictions</a></li>
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<p class="first admonition-title">Note</p>
<p class="last">Click <a class="reference internal" href="#sphx-glr-download-auto-examples-ensemble-plot-voting-regressor-py"><span class="std std-ref">here</span></a> to download the full example code</p>
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<div class="sphx-glr-example-title section" id="plot-individual-and-voting-regression-predictions">
<span id="sphx-glr-auto-examples-ensemble-plot-voting-regressor-py"></span><h1>Plot individual and voting regression predictions<a class="headerlink" href="#plot-individual-and-voting-regression-predictions" title="Permalink to this headline">¶</a></h1>
<p>Plot individual and averaged regression predictions for Boston dataset.</p>
<p>First, three exemplary regressors are initialized (<a class="reference internal" href="../../modules/generated/sklearn.ensemble.GradientBoostingRegressor.html#sklearn.ensemble.GradientBoostingRegressor" title="sklearn.ensemble.GradientBoostingRegressor"><code class="xref any py py-class docutils literal"><span class="pre">GradientBoostingRegressor</span></code></a>,
<a class="reference internal" href="../../modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor" title="sklearn.ensemble.RandomForestRegressor"><code class="xref any py py-class docutils literal"><span class="pre">RandomForestRegressor</span></code></a>, and <a class="reference internal" href="../../modules/generated/sklearn.linear_model.LinearRegression.html#sklearn.linear_model.LinearRegression" title="sklearn.linear_model.LinearRegression"><code class="xref any py py-class docutils literal"><span class="pre">LinearRegression</span></code></a>) and used to initialize a
<a class="reference internal" href="../../modules/generated/sklearn.ensemble.VotingRegressor.html#sklearn.ensemble.VotingRegressor" title="sklearn.ensemble.VotingRegressor"><code class="xref any py py-class docutils literal"><span class="pre">VotingRegressor</span></code></a>.</p>
<p>The red starred dots are the averaged predictions.</p>
<img alt="../../_images/sphx_glr_plot_voting_regressor_001.png" class="sphx-glr-single-img" src="../../_images/sphx_glr_plot_voting_regressor_001.png" />
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">print</span><span class="p">(</span><span class="vm">__doc__</span><span class="p">)</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</span> <span class="kn">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.ensemble.GradientBoostingRegressor.html#sklearn.ensemble.GradientBoostingRegressor" title="View documentation for sklearn.ensemble.GradientBoostingRegressor"><span class="n">GradientBoostingRegressor</span></a>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor" title="View documentation for sklearn.ensemble.RandomForestRegressor"><span class="n">RandomForestRegressor</span></a>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.linear_model.LinearRegression.html#sklearn.linear_model.LinearRegression" title="View documentation for sklearn.linear_model.LinearRegression"><span class="n">LinearRegression</span></a>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.ensemble.VotingRegressor.html#sklearn.ensemble.VotingRegressor" title="View documentation for sklearn.ensemble.VotingRegressor"><span class="n">VotingRegressor</span></a>
<span class="c1"># Loading some example data</span>
<span class="n">boston</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.datasets.load_boston.html#sklearn.datasets.load_boston" title="View documentation for sklearn.datasets.load_boston"><span class="n">datasets</span><span class="o">.</span><span class="n">load_boston</span></a><span class="p">()</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">boston</span><span class="o">.</span><span class="n">data</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">boston</span><span class="o">.</span><span class="n">target</span>
<span class="c1"># Training classifiers</span>
<span class="n">reg1</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.ensemble.GradientBoostingRegressor.html#sklearn.ensemble.GradientBoostingRegressor" title="View documentation for sklearn.ensemble.GradientBoostingRegressor"><span class="n">GradientBoostingRegressor</span></a><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_estimators</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">reg2</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.ensemble.RandomForestRegressor.html#sklearn.ensemble.RandomForestRegressor" title="View documentation for sklearn.ensemble.RandomForestRegressor"><span class="n">RandomForestRegressor</span></a><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_estimators</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">reg3</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.linear_model.LinearRegression.html#sklearn.linear_model.LinearRegression" title="View documentation for sklearn.linear_model.LinearRegression"><span class="n">LinearRegression</span></a><span class="p">()</span>
<span class="n">ereg</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.ensemble.VotingRegressor.html#sklearn.ensemble.VotingRegressor" title="View documentation for sklearn.ensemble.VotingRegressor"><span class="n">VotingRegressor</span></a><span class="p">([(</span><span class="s1">'gb'</span><span class="p">,</span> <span class="n">reg1</span><span class="p">),</span> <span class="p">(</span><span class="s1">'rf'</span><span class="p">,</span> <span class="n">reg2</span><span class="p">),</span> <span class="p">(</span><span class="s1">'lr'</span><span class="p">,</span> <span class="n">reg3</span><span class="p">)])</span>
<span class="n">reg1</span><span class="o">.</span><span class="n">fit</span><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">reg2</span><span class="o">.</span><span class="n">fit</span><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">reg3</span><span class="o">.</span><span class="n">fit</span><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">ereg</span><span class="o">.</span><span class="n">fit</span><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">xt</span> <span class="o">=</span> <span class="n">X</span><span class="p">[:</span><span class="mi">20</span><span class="p">]</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.figure.html#matplotlib.pyplot.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>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot"><span class="n">plt</span><span class="o">.</span><span class="n">plot</span></a><span class="p">(</span><span class="n">reg1</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">xt</span><span class="p">),</span> <span class="s1">'gd'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'GradientBoostingRegressor'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot"><span class="n">plt</span><span class="o">.</span><span class="n">plot</span></a><span class="p">(</span><span class="n">reg2</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">xt</span><span class="p">),</span> <span class="s1">'b^'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'RandomForestRegressor'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot"><span class="n">plt</span><span class="o">.</span><span class="n">plot</span></a><span class="p">(</span><span class="n">reg3</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">xt</span><span class="p">),</span> <span class="s1">'ys'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'LinearRegression'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html#matplotlib.pyplot.plot" title="View documentation for matplotlib.pyplot.plot"><span class="n">plt</span><span class="o">.</span><span class="n">plot</span></a><span class="p">(</span><span class="n">ereg</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">xt</span><span class="p">),</span> <span class="s1">'r*'</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">'VotingRegressor'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.tick_params.html#matplotlib.pyplot.tick_params" title="View documentation for matplotlib.pyplot.tick_params"><span class="n">plt</span><span class="o">.</span><span class="n">tick_params</span></a><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="s1">'x'</span><span class="p">,</span> <span class="n">which</span><span class="o">=</span><span class="s1">'both'</span><span class="p">,</span> <span class="n">bottom</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">top</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span>
<span class="n">labelbottom</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<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">'predicted'</span><span class="p">)</span>
<a href="https://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">'training samples'</span><span class="p">)</span>
<a href="https://matplotlib.org/api/_as_gen/matplotlib.pyplot.legend.html#matplotlib.pyplot.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="s2">"best"</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">'Comparison of individual predictions with averaged'</span><span class="p">)</span>
<a href="https://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>
</pre></div>
</div>
<p><strong>Total running time of the script:</strong> ( 0 minutes 0.117 seconds)</p>
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