Rebuild dev docs at master=d52e2a1

Author: sklearn-ci

dev/modules/generated/sklearn.cluster.AgglomerativeClustering.html

@@ -132,7 +132,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.cluster" title="sklearn.cluster"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.cluster</span></code></a>.AgglomerativeClustering<a class="headerlink" href="#sklearn-cluster-agglomerativeclustering" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.cluster.AgglomerativeClustering">
-<em class="property">class </em><code class="descclassname">sklearn.cluster.</code><code class="descname">AgglomerativeClustering</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2342aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L607"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.AgglomerativeClustering" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">sklearn.cluster.</code><code class="descname">AgglomerativeClustering</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2127aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L607"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.AgglomerativeClustering" title="Permalink to this definition">¶</a></dt>
 <dd><p>Agglomerative Clustering</p>
 <p>Recursively merges the pair of clusters that minimally increases
 a given linkage distance.</p>
@@ -239,7 +239,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.cluster"
 </table>
 <dl class="method">
 <dt id="sklearn.cluster.AgglomerativeClustering.__init__">
-<code class="descname">__init__</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2342aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L690"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.AgglomerativeClustering.__init__" title="Permalink to this definition">¶</a></dt>
+<code class="descname">__init__</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2127aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L690"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.AgglomerativeClustering.__init__" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
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dev/modules/generated/sklearn.cluster.FeatureAgglomeration.html

@@ -132,7 +132,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.cluster" title="sklearn.cluster"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.cluster</span></code></a>.FeatureAgglomeration<a class="headerlink" href="#sklearn-cluster-featureagglomeration" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.cluster.FeatureAgglomeration">
-<em class="property">class </em><code class="descclassname">sklearn.cluster.</code><code class="descname">FeatureAgglomeration</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2342aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L779"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.FeatureAgglomeration" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">sklearn.cluster.</code><code class="descname">FeatureAgglomeration</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2127aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L779"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.FeatureAgglomeration" title="Permalink to this definition">¶</a></dt>
 <dd><p>Agglomerate features.</p>
 <p>Similar to AgglomerativeClustering, but recursively merges features
 instead of samples.</p>
@@ -239,7 +239,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.cluster"
 </table>
 <dl class="method">
 <dt id="sklearn.cluster.FeatureAgglomeration.__init__">
-<code class="descname">__init__</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2342aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L690"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.FeatureAgglomeration.__init__" title="Permalink to this definition">¶</a></dt>
+<code class="descname">__init__</code><span class="sig-paren">(</span><em>n_clusters=2</em>, <em>affinity='euclidean'</em>, <em>memory=Memory(cachedir=None)</em>, <em>connectivity=None</em>, <em>n_components=None</em>, <em>compute_full_tree='auto'</em>, <em>linkage='ward'</em>, <em>pooling_func=&lt;function mean at 0x2127aa0&gt;</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/cluster/hierarchical.py#L690"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.cluster.FeatureAgglomeration.__init__" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
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dev/modules/generated/sklearn.feature_selection.SelectKBest.html

@@ -132,7 +132,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.feature_selection" title="sklearn.feature_selection"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.feature_selection</span></code></a>.SelectKBest<a class="headerlink" href="#sklearn-feature-selection-selectkbest" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.feature_selection.SelectKBest">
-<em class="property">class </em><code class="descclassname">sklearn.feature_selection.</code><code class="descname">SelectKBest</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5c58848&gt;</em>, <em>k=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L412"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectKBest" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">sklearn.feature_selection.</code><code class="descname">SelectKBest</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5a3f848&gt;</em>, <em>k=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L412"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectKBest" title="Permalink to this definition">¶</a></dt>
 <dd><p>Select features according to the k highest scores.</p>
 <p>Read more in the <a class="reference internal" href="../feature_selection.html#univariate-feature-selection"><span>User Guide</span></a>.</p>
 <table class="docutils field-list" frame="void" rules="none">
@@ -198,7 +198,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.feature_s
 </table>
 <dl class="method">
 <dt id="sklearn.feature_selection.SelectKBest.__init__">
-<code class="descname">__init__</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5c58848&gt;</em>, <em>k=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L452"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectKBest.__init__" title="Permalink to this definition">¶</a></dt>
+<code class="descname">__init__</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5a3f848&gt;</em>, <em>k=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L452"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectKBest.__init__" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="method">

dev/modules/generated/sklearn.feature_selection.SelectPercentile.html

@@ -132,7 +132,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.feature_selection" title="sklearn.feature_selection"><code class="xref py py-mod docutils literal"><span class="pre">sklearn.feature_selection</span></code></a>.SelectPercentile<a class="headerlink" href="#sklearn-feature-selection-selectpercentile" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.feature_selection.SelectPercentile">
-<em class="property">class </em><code class="descclassname">sklearn.feature_selection.</code><code class="descname">SelectPercentile</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5c58848&gt;</em>, <em>percentile=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L343"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectPercentile" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">sklearn.feature_selection.</code><code class="descname">SelectPercentile</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5a3f848&gt;</em>, <em>percentile=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L343"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectPercentile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Select features according to a percentile of the highest scores.</p>
 <p>Read more in the <a class="reference internal" href="../feature_selection.html#univariate-feature-selection"><span>User Guide</span></a>.</p>
 <table class="docutils field-list" frame="void" rules="none">
@@ -197,7 +197,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.feature_s
 </table>
 <dl class="method">
 <dt id="sklearn.feature_selection.SelectPercentile.__init__">
-<code class="descname">__init__</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5c58848&gt;</em>, <em>percentile=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L382"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectPercentile.__init__" title="Permalink to this definition">¶</a></dt>
+<code class="descname">__init__</code><span class="sig-paren">(</span><em>score_func=&lt;function f_classif at 0x5a3f848&gt;</em>, <em>percentile=10</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/d52e2a1/sklearn/feature_selection/univariate_selection.py#L382"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.feature_selection.SelectPercentile.__init__" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="method">