Rebuild dev docs at master=c60f72b

Author: sklearn-ci

dev/_sources/developers/contributing.txt

@@ -214,7 +214,7 @@ Easy Issues
 
 A great way to start contributing to scikit-learn is to pick an item from the
 list of `Easy issues
-<https://github.com/scikit-learn/scikit-learn/labels/Easy>`_
+<https://github.com/scikit-learn/scikit-learn/issues?q=is%3Aopen+label%3AEasy+is%3Aissue>`_
 in the issue tracker. Resolving these issues allow you to start contributing
 to the project without much prior knowledge. Your assistance in this area will
 be greatly appreciated by the more experienced developers as it helps free up

dev/developers/contributing.html

@@ -411,7 +411,7 @@ <h3>How to contribute<a class="headerlink" href="#how-to-contribute" title="Perm
 <div class="section" id="easy-issues">
 <span id="id2"></span><h3>Easy Issues<a class="headerlink" href="#easy-issues" title="Permalink to this headline">¶</a></h3>
 <p>A great way to start contributing to scikit-learn is to pick an item from the
-list of <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/labels/Easy">Easy issues</a>
+list of <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues?q=is%3Aopen+label%3AEasy+is%3Aissue">Easy issues</a>
 in the issue tracker. Resolving these issues allow you to start contributing
 to the project without much prior knowledge. Your assistance in this area will
 be greatly appreciated by the more experienced developers as it helps free up

dev/modules/generated/sklearn.base.BaseEstimator.html

@@ -172,7 +172,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.base" title="sklearn.base"><tt class="xref py py-mod docutils literal"><span class="pre">sklearn.base</span></tt></a>.BaseEstimator<a class="headerlink" href="#sklearn-base-baseestimator" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.base.BaseEstimator">
-<em class="property">class </em><tt class="descclassname">sklearn.base.</tt><tt class="descname">BaseEstimator</tt><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L169"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><tt class="descclassname">sklearn.base.</tt><tt class="descname">BaseEstimator</tt><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L169"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator" title="Permalink to this definition">¶</a></dt>
 <dd><p>Base class for all estimators in scikit-learn</p>
 <p class="rubric">Notes</p>
 <p>All estimators should specify all the parameters that can be set
@@ -201,7 +201,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.base" tit
 
 <dl class="method">
 <dt id="sklearn.base.BaseEstimator.get_params">
-<tt class="descname">get_params</tt><big>(</big><em>deep=True</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L206"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator.get_params" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">get_params</tt><big>(</big><em>deep=True</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L206"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator.get_params" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get parameters for this estimator.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -226,7 +226,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.base" tit
 
 <dl class="method">
 <dt id="sklearn.base.BaseEstimator.set_params">
-<tt class="descname">set_params</tt><big>(</big><em>**params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L243"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator.set_params" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">set_params</tt><big>(</big><em>**params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L243"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.BaseEstimator.set_params" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set the parameters of this estimator.</p>
 <p>The method works on simple estimators as well as on nested objects
 (such as pipelines). The former have parameters of the form

dev/modules/generated/sklearn.base.TransformerMixin.html

@@ -172,7 +172,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.base" title="sklearn.base"><tt class="xref py py-mod docutils literal"><span class="pre">sklearn.base</span></tt></a>.TransformerMixin<a class="headerlink" href="#sklearn-base-transformermixin" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.base.TransformerMixin">
-<em class="property">class </em><tt class="descclassname">sklearn.base.</tt><tt class="descname">TransformerMixin</tt><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L435"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.TransformerMixin" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><tt class="descclassname">sklearn.base.</tt><tt class="descname">TransformerMixin</tt><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L435"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.TransformerMixin" title="Permalink to this definition">¶</a></dt>
 <dd><p>Mixin class for all transformers in scikit-learn.</p>
 <p class="rubric">Methods</p>
 <table border="1" class="longtable docutils">
@@ -194,7 +194,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.base" tit
 
 <dl class="method">
 <dt id="sklearn.base.TransformerMixin.fit_transform">
-<tt class="descname">fit_transform</tt><big>(</big><em>X</em>, <em>y=None</em>, <em>**fit_params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L438"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.TransformerMixin.fit_transform" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">fit_transform</tt><big>(</big><em>X</em>, <em>y=None</em>, <em>**fit_params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L438"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.base.TransformerMixin.fit_transform" title="Permalink to this definition">¶</a></dt>
 <dd><p>Fit to data, then transform it.</p>
 <p>Fits transformer to X and y with optional parameters fit_params
 and returns a transformed version of X.</p>

dev/modules/generated/sklearn.calibration.CalibratedClassifierCV.html

@@ -172,7 +172,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.calibration" title="sklearn.calibration"><tt class="xref py py-mod docutils literal"><span class="pre">sklearn.calibration</span></tt></a>.CalibratedClassifierCV<a class="headerlink" href="#sklearn-calibration-calibratedclassifiercv" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="sklearn.calibration.CalibratedClassifierCV">
-<em class="property">class </em><tt class="descclassname">sklearn.calibration.</tt><tt class="descname">CalibratedClassifierCV</tt><big>(</big><em>base_estimator=None</em>, <em>method='sigmoid'</em>, <em>cv=3</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L29"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><tt class="descclassname">sklearn.calibration.</tt><tt class="descname">CalibratedClassifierCV</tt><big>(</big><em>base_estimator=None</em>, <em>method='sigmoid'</em>, <em>cv=3</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L29"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV" title="Permalink to this definition">¶</a></dt>
 <dd><p>Probability calibration with isotonic regression or sigmoid.</p>
 <p>With this class, the base_estimator is fit on the train set of the
 cross-validation generator and the test set is used for calibration.
@@ -294,12 +294,12 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 </table>
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.__init__">
-<tt class="descname">__init__</tt><big>(</big><em>base_estimator=None</em>, <em>method='sigmoid'</em>, <em>cv=3</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L98"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.__init__" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">__init__</tt><big>(</big><em>base_estimator=None</em>, <em>method='sigmoid'</em>, <em>cv=3</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L98"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.__init__" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.fit">
-<tt class="descname">fit</tt><big>(</big><em>X</em>, <em>y</em>, <em>sample_weight=None</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L103"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.fit" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">fit</tt><big>(</big><em>X</em>, <em>y</em>, <em>sample_weight=None</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L103"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.fit" title="Permalink to this definition">¶</a></dt>
 <dd><p>Fit the calibrated model</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -331,7 +331,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.get_params">
-<tt class="descname">get_params</tt><big>(</big><em>deep=True</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L206"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.get_params" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">get_params</tt><big>(</big><em>deep=True</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L206"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.get_params" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get parameters for this estimator.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -356,7 +356,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.predict">
-<tt class="descname">predict</tt><big>(</big><em>X</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L216"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.predict" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">predict</tt><big>(</big><em>X</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L216"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.predict" title="Permalink to this definition">¶</a></dt>
 <dd><p>Predict the target of new samples. Can be different from the
 prediction of the uncalibrated classifier.</p>
 <table class="docutils field-list" frame="void" rules="none">
@@ -381,7 +381,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.predict_proba">
-<tt class="descname">predict_proba</tt><big>(</big><em>X</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L186"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.predict_proba" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">predict_proba</tt><big>(</big><em>X</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L186"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.predict_proba" title="Permalink to this definition">¶</a></dt>
 <dd><p>Posterior probabilities of classification</p>
 <p>This function returns posterior probabilities of classification
 according to each class on an array of test vectors X.</p>
@@ -407,7 +407,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.score">
-<tt class="descname">score</tt><big>(</big><em>X</em>, <em>y</em>, <em>sample_weight=None</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L292"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.score" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">score</tt><big>(</big><em>X</em>, <em>y</em>, <em>sample_weight=None</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L292"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.score" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns the mean accuracy on the given test data and labels.</p>
 <p>In multi-label classification, this is the subset accuracy
 which is a harsh metric since you require for each sample that
@@ -442,7 +442,7 @@ <h1><a class="reference internal" href="../classes.html#module-sklearn.calibrati
 
 <dl class="method">
 <dt id="sklearn.calibration.CalibratedClassifierCV.set_params">
-<tt class="descname">set_params</tt><big>(</big><em>**params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/base.py#L243"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.set_params" title="Permalink to this definition">¶</a></dt>
+<tt class="descname">set_params</tt><big>(</big><em>**params</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/base.py#L243"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.CalibratedClassifierCV.set_params" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set the parameters of this estimator.</p>
 <p>The method works on simple estimators as well as on nested objects
 (such as pipelines). The former have parameters of the form

dev/modules/generated/sklearn.calibration.calibration_curve.html

@@ -172,7 +172,7 @@
 <h1><a class="reference internal" href="../classes.html#module-sklearn.calibration" title="sklearn.calibration"><tt class="xref py py-mod docutils literal"><span class="pre">sklearn.calibration</span></tt></a>.calibration_curve<a class="headerlink" href="#sklearn-calibration-calibration-curve" title="Permalink to this headline">¶</a></h1>
 <dl class="function">
 <dt id="sklearn.calibration.calibration_curve">
-<tt class="descclassname">sklearn.calibration.</tt><tt class="descname">calibration_curve</tt><big>(</big><em>y_true</em>, <em>y_prob</em>, <em>normalize=False</em>, <em>n_bins=5</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/23f2891/sklearn/calibration.py#L491"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.calibration_curve" title="Permalink to this definition">¶</a></dt>
+<tt class="descclassname">sklearn.calibration.</tt><tt class="descname">calibration_curve</tt><big>(</big><em>y_true</em>, <em>y_prob</em>, <em>normalize=False</em>, <em>n_bins=5</em><big>)</big><a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/c60f72b/sklearn/calibration.py#L491"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#sklearn.calibration.calibration_curve" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute true and predicted probabilities for a calibration curve.</p>
 <p>Read more in the <a class="reference internal" href="../calibration.html#calibration"><em>User Guide</em></a>.</p>
 <table class="docutils field-list" frame="void" rules="none">