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<title>10. Collectors &amp; Extractors &#8212; MIPLearn 0.3</title>
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<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#module-miplearn.classifiers.minprob">
10.1. miplearn.classifiers.minprob
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#module-miplearn.classifiers.singleclass">
10.2. miplearn.classifiers.singleclass
</a>
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<a class="reference internal nav-link" href="#module-miplearn.collectors.basic">
10.3. miplearn.collectors.basic
</a>
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<a class="reference internal nav-link" href="#module-miplearn.extractors.fields">
10.4. miplearn.extractors.fields
</a>
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<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#module-miplearn.extractors.AlvLouWeh2017">
10.5. miplearn.extractors.AlvLouWeh2017
</a>
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<div class="section" id="collectors-extractors">
<h1><span class="section-number">10. </span>Collectors &amp; Extractors<a class="headerlink" href="#collectors-extractors" title="Permalink to this headline"></a></h1>
<div class="section" id="module-miplearn.classifiers.minprob">
<span id="miplearn-classifiers-minprob"></span><h2><span class="section-number">10.1. </span>miplearn.classifiers.minprob<a class="headerlink" href="#module-miplearn.classifiers.minprob" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt id="miplearn.classifiers.minprob.MinProbabilityClassifier">
<em class="property"><span class="pre">class</span> </em><code class="sig-prename descclassname"><span class="pre">miplearn.classifiers.minprob.</span></code><code class="sig-name descname"><span class="pre">MinProbabilityClassifier</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="pre">base_clf:</span> <span class="pre">Any,</span> <span class="pre">thresholds:</span> <span class="pre">List[float],</span> <span class="pre">clone_fn:</span> <span class="pre">Callable[[Any],</span> <span class="pre">Any]</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">clone&gt;</span></em><span class="sig-paren">)</span><a class="headerlink" href="#miplearn.classifiers.minprob.MinProbabilityClassifier" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.base.BaseEstimator</span></code></p>
<p>Meta-classifier that returns NaN for predictions made by a base classifier that
have probability below a given threshold. More specifically, this meta-classifier
calls base_clf.predict_proba and compares the result against the provided
thresholds. If the probability for one of the classes is above its threshold,
the meta-classifier returns that prediction. Otherwise, it returns NaN.</p>
<dl class="py method">
<dt id="miplearn.classifiers.minprob.MinProbabilityClassifier.fit">
<code class="sig-name descname"><span class="pre">fit</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">None</span><a class="headerlink" href="#miplearn.classifiers.minprob.MinProbabilityClassifier.fit" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.classifiers.minprob.MinProbabilityClassifier.predict">
<code class="sig-name descname"><span class="pre">predict</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.classifiers.minprob.MinProbabilityClassifier.predict" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-miplearn.classifiers.singleclass">
<span id="miplearn-classifiers-singleclass"></span><h2><span class="section-number">10.2. </span>miplearn.classifiers.singleclass<a class="headerlink" href="#module-miplearn.classifiers.singleclass" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt id="miplearn.classifiers.singleclass.SingleClassFix">
<em class="property"><span class="pre">class</span> </em><code class="sig-prename descclassname"><span class="pre">miplearn.classifiers.singleclass.</span></code><code class="sig-name descname"><span class="pre">SingleClassFix</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="pre">base_clf:</span> <span class="pre">sklearn.base.BaseEstimator</span></em>, <em class="sig-param"><span class="pre">clone_fn:</span> <span class="pre">Callable</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">clone&gt;</span></em><span class="sig-paren">)</span><a class="headerlink" href="#miplearn.classifiers.singleclass.SingleClassFix" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">sklearn.base.BaseEstimator</span></code></p>
<p>Some sklearn classifiers, such as logistic regression, have issues with datasets
that contain a single class. This meta-classifier fixes the issue. If the
training data contains a single class, this meta-classifier always returns that
class as a prediction. Otherwise, it fits the provided base classifier,
and returns its predictions instead.</p>
<dl class="py method">
<dt id="miplearn.classifiers.singleclass.SingleClassFix.fit">
<code class="sig-name descname"><span class="pre">fit</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">y</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">None</span><a class="headerlink" href="#miplearn.classifiers.singleclass.SingleClassFix.fit" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.classifiers.singleclass.SingleClassFix.predict">
<code class="sig-name descname"><span class="pre">predict</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.classifiers.singleclass.SingleClassFix.predict" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-miplearn.collectors.basic">
<span id="miplearn-collectors-basic"></span><h2><span class="section-number">10.3. </span>miplearn.collectors.basic<a class="headerlink" href="#module-miplearn.collectors.basic" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt id="miplearn.collectors.basic.BasicCollector">
<em class="property"><span class="pre">class</span> </em><code class="sig-prename descclassname"><span class="pre">miplearn.collectors.basic.</span></code><code class="sig-name descname"><span class="pre">BasicCollector</span></code><a class="headerlink" href="#miplearn.collectors.basic.BasicCollector" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<dl class="py method">
<dt id="miplearn.collectors.basic.BasicCollector.collect">
<code class="sig-name descname"><span class="pre">collect</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filenames</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">build_model</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_jobs</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">progress</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">None</span><a class="headerlink" href="#miplearn.collectors.basic.BasicCollector.collect" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-miplearn.extractors.fields">
<span id="miplearn-extractors-fields"></span><h2><span class="section-number">10.4. </span>miplearn.extractors.fields<a class="headerlink" href="#module-miplearn.extractors.fields" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt id="miplearn.extractors.fields.H5FieldsExtractor">
<em class="property"><span class="pre">class</span> </em><code class="sig-prename descclassname"><span class="pre">miplearn.extractors.fields.</span></code><code class="sig-name descname"><span class="pre">H5FieldsExtractor</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instance_fields</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">var_fields</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">constr_fields</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#miplearn.extractors.fields.H5FieldsExtractor" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">miplearn.extractors.abstract.FeaturesExtractor</span></code></p>
<dl class="py method">
<dt id="miplearn.extractors.fields.H5FieldsExtractor.get_constr_features">
<code class="sig-name descname"><span class="pre">get_constr_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.fields.H5FieldsExtractor.get_constr_features" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.extractors.fields.H5FieldsExtractor.get_instance_features">
<code class="sig-name descname"><span class="pre">get_instance_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.fields.H5FieldsExtractor.get_instance_features" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.extractors.fields.H5FieldsExtractor.get_var_features">
<code class="sig-name descname"><span class="pre">get_var_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.fields.H5FieldsExtractor.get_var_features" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-miplearn.extractors.AlvLouWeh2017">
<span id="miplearn-extractors-alvlouweh2017"></span><h2><span class="section-number">10.5. </span>miplearn.extractors.AlvLouWeh2017<a class="headerlink" href="#module-miplearn.extractors.AlvLouWeh2017" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt id="miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor">
<em class="property"><span class="pre">class</span> </em><code class="sig-prename descclassname"><span class="pre">miplearn.extractors.AlvLouWeh2017.</span></code><code class="sig-name descname"><span class="pre">AlvLouWeh2017Extractor</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">with_m1</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">with_m2</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">with_m3</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">miplearn.extractors.abstract.FeaturesExtractor</span></code></p>
<dl class="py method">
<dt id="miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_constr_features">
<code class="sig-name descname"><span class="pre">get_constr_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_constr_features" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_instance_features">
<code class="sig-name descname"><span class="pre">get_instance_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_instance_features" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_var_features">
<code class="sig-name descname"><span class="pre">get_var_features</span></code><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">h5</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="../helpers/#miplearn.h5.H5File" title="miplearn.h5.H5File"><span class="pre">miplearn.h5.H5File</span></a></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.ndarray</span><a class="headerlink" href="#miplearn.extractors.AlvLouWeh2017.AlvLouWeh2017Extractor.get_var_features" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>Computes static variable features described in:</dt><dd><p>Alvarez, A. M., Louveaux, Q., &amp; Wehenkel, L. (2017). A machine learning-based
approximation of strong branching. INFORMS Journal on Computing, 29(1),
185-195.</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
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