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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.mixture.html">sklearn.mixture</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.model_selection.html">sklearn.model_selection</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.multiclass.html">sklearn.multiclass</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.multioutput.html">sklearn.multioutput</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.naive_bayes.html">sklearn.naive_bayes</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.neighbors.html">sklearn.neighbors</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.neural_network.html">sklearn.neural_network</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="sklearn.pipeline.html">sklearn.pipeline</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 current active has-children"><a class="current reference internal" href="#">sklearn.preprocessing</a><details open="open"><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="../modules/generated/sklearn.preprocessing.Binarizer.html">Binarizer</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../modules/generated/sklearn.preprocessing.OneHotEncoder.html">OneHotEncoder</a></li>
<li class="toctree-l2"><a class="reference internal" href="../modules/generated/sklearn.preprocessing.OrdinalEncoder.html">OrdinalEncoder</a></li>
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  <section id="module-sklearn.preprocessing">
<span id="sklearn-preprocessing"></span><span id="preprocessing-ref"></span><h1>sklearn.preprocessing<a class="headerlink" href="#module-sklearn.preprocessing" title="Link to this heading">#</a></h1>
<p>Methods for scaling, centering, normalization, binarization, and more.</p>
<p><strong>User guide.</strong> See the <a class="reference internal" href="../modules/preprocessing.html#preprocessing"><span class="std std-ref">Preprocessing data</span></a> section for further details.</p>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.Binarizer.html#sklearn.preprocessing.Binarizer" title="sklearn.preprocessing.Binarizer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Binarizer</span></code></a></p></td>
<td><p>Binarize data (set feature values to 0 or 1) according to a threshold.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.FunctionTransformer.html#sklearn.preprocessing.FunctionTransformer" title="sklearn.preprocessing.FunctionTransformer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FunctionTransformer</span></code></a></p></td>
<td><p>Constructs a transformer from an arbitrary callable.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.KBinsDiscretizer.html#sklearn.preprocessing.KBinsDiscretizer" title="sklearn.preprocessing.KBinsDiscretizer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">KBinsDiscretizer</span></code></a></p></td>
<td><p>Bin continuous data into intervals.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.KernelCenterer.html#sklearn.preprocessing.KernelCenterer" title="sklearn.preprocessing.KernelCenterer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">KernelCenterer</span></code></a></p></td>
<td><p>Center an arbitrary kernel matrix <span class="math notranslate nohighlight">\(K\)</span>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.LabelBinarizer.html#sklearn.preprocessing.LabelBinarizer" title="sklearn.preprocessing.LabelBinarizer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LabelBinarizer</span></code></a></p></td>
<td><p>Binarize labels in a one-vs-all fashion.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.LabelEncoder.html#sklearn.preprocessing.LabelEncoder" title="sklearn.preprocessing.LabelEncoder"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LabelEncoder</span></code></a></p></td>
<td><p>Encode target labels with value between 0 and n_classes-1.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.MaxAbsScaler.html#sklearn.preprocessing.MaxAbsScaler" title="sklearn.preprocessing.MaxAbsScaler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MaxAbsScaler</span></code></a></p></td>
<td><p>Scale each feature by its maximum absolute value.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.MinMaxScaler.html#sklearn.preprocessing.MinMaxScaler" title="sklearn.preprocessing.MinMaxScaler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MinMaxScaler</span></code></a></p></td>
<td><p>Transform features by scaling each feature to a given range.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.MultiLabelBinarizer.html#sklearn.preprocessing.MultiLabelBinarizer" title="sklearn.preprocessing.MultiLabelBinarizer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MultiLabelBinarizer</span></code></a></p></td>
<td><p>Transform between iterable of iterables and a multilabel format.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.Normalizer.html#sklearn.preprocessing.Normalizer" title="sklearn.preprocessing.Normalizer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Normalizer</span></code></a></p></td>
<td><p>Normalize samples individually to unit norm.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder" title="sklearn.preprocessing.OneHotEncoder"><code class="xref py py-obj docutils literal notranslate"><span class="pre">OneHotEncoder</span></code></a></p></td>
<td><p>Encode categorical features as a one-hot numeric array.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.OrdinalEncoder.html#sklearn.preprocessing.OrdinalEncoder" title="sklearn.preprocessing.OrdinalEncoder"><code class="xref py py-obj docutils literal notranslate"><span class="pre">OrdinalEncoder</span></code></a></p></td>
<td><p>Encode categorical features as an integer array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.PolynomialFeatures.html#sklearn.preprocessing.PolynomialFeatures" title="sklearn.preprocessing.PolynomialFeatures"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PolynomialFeatures</span></code></a></p></td>
<td><p>Generate polynomial and interaction features.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.PowerTransformer.html#sklearn.preprocessing.PowerTransformer" title="sklearn.preprocessing.PowerTransformer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">PowerTransformer</span></code></a></p></td>
<td><p>Apply a power transform featurewise to make data more Gaussian-like.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.QuantileTransformer.html#sklearn.preprocessing.QuantileTransformer" title="sklearn.preprocessing.QuantileTransformer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">QuantileTransformer</span></code></a></p></td>
<td><p>Transform features using quantiles information.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.RobustScaler.html#sklearn.preprocessing.RobustScaler" title="sklearn.preprocessing.RobustScaler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">RobustScaler</span></code></a></p></td>
<td><p>Scale features using statistics that are robust to outliers.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.SplineTransformer.html#sklearn.preprocessing.SplineTransformer" title="sklearn.preprocessing.SplineTransformer"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SplineTransformer</span></code></a></p></td>
<td><p>Generate univariate B-spline bases for features.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.StandardScaler.html#sklearn.preprocessing.StandardScaler" title="sklearn.preprocessing.StandardScaler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">StandardScaler</span></code></a></p></td>
<td><p>Standardize features by removing the mean and scaling to unit variance.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.TargetEncoder.html#sklearn.preprocessing.TargetEncoder" title="sklearn.preprocessing.TargetEncoder"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TargetEncoder</span></code></a></p></td>
<td><p>Target Encoder for regression and classification targets.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.add_dummy_feature.html#sklearn.preprocessing.add_dummy_feature" title="sklearn.preprocessing.add_dummy_feature"><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_dummy_feature</span></code></a></p></td>
<td><p>Augment dataset with an additional dummy feature.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.binarize.html#sklearn.preprocessing.binarize" title="sklearn.preprocessing.binarize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">binarize</span></code></a></p></td>
<td><p>Boolean thresholding of array-like or scipy.sparse matrix.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.label_binarize.html#sklearn.preprocessing.label_binarize" title="sklearn.preprocessing.label_binarize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">label_binarize</span></code></a></p></td>
<td><p>Binarize labels in a one-vs-all fashion.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.maxabs_scale.html#sklearn.preprocessing.maxabs_scale" title="sklearn.preprocessing.maxabs_scale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">maxabs_scale</span></code></a></p></td>
<td><p>Scale each feature to the [-1, 1] range without breaking the sparsity.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.minmax_scale.html#sklearn.preprocessing.minmax_scale" title="sklearn.preprocessing.minmax_scale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">minmax_scale</span></code></a></p></td>
<td><p>Transform features by scaling each feature to a given range.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.normalize.html#sklearn.preprocessing.normalize" title="sklearn.preprocessing.normalize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">normalize</span></code></a></p></td>
<td><p>Scale input vectors individually to unit norm (vector length).</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.power_transform.html#sklearn.preprocessing.power_transform" title="sklearn.preprocessing.power_transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">power_transform</span></code></a></p></td>
<td><p>Parametric, monotonic transformation to make data more Gaussian-like.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.quantile_transform.html#sklearn.preprocessing.quantile_transform" title="sklearn.preprocessing.quantile_transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">quantile_transform</span></code></a></p></td>
<td><p>Transform features using quantiles information.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.robust_scale.html#sklearn.preprocessing.robust_scale" title="sklearn.preprocessing.robust_scale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">robust_scale</span></code></a></p></td>
<td><p>Standardize a dataset along any axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="../modules/generated/sklearn.preprocessing.scale.html#sklearn.preprocessing.scale" title="sklearn.preprocessing.scale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">scale</span></code></a></p></td>
<td><p>Standardize a dataset along any axis.</p></td>
</tr>
</tbody>
</table>
</div>
</section>


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