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<section id="miscellaneous">
<span id="miscellaneous-examples"></span><span id="sphx-glr-auto-examples-miscellaneous"></span><h1>Miscellaneous<a class="headerlink" href="#miscellaneous" title="Permalink to this heading">¶</a></h1>
<p>Miscellaneous and introductory examples for scikit-learn.</p>
<div class="sphx-glr-thumbnails"><div class="sphx-glr-thumbcontainer" tooltip=" See also sphx_glr_auto_examples_miscellaneous_plot_roc_curve_visualization_api.py"><img alt="Advanced Plotting With Partial Dependence" src="../../_images/sphx_glr_plot_partial_dependence_visualization_api_thumb.png" />
<p><a class="reference internal" href="plot_partial_dependence_visualization_api.html#sphx-glr-auto-examples-miscellaneous-plot-partial-dependence-visualization-api-py"><span class="std std-ref">Advanced Plotting With Partial Dependence</span></a></p>
<div class="sphx-glr-thumbnail-title">Advanced Plotting With Partial Dependence</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example shows characteristics of different anomaly detection algorithms on 2D datasets. Da..."><img alt="Comparing anomaly detection algorithms for outlier detection on toy datasets" src="../../_images/sphx_glr_plot_anomaly_comparison_thumb.png" />
<p><a class="reference internal" href="plot_anomaly_comparison.html#sphx-glr-auto-examples-miscellaneous-plot-anomaly-comparison-py"><span class="std std-ref">Comparing anomaly detection algorithms for outlier detection on toy datasets</span></a></p>
<div class="sphx-glr-thumbnail-title">Comparing anomaly detection algorithms for outlier detection on toy datasets</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="Both kernel ridge regression (KRR) and SVR learn a non-linear function by employing the kernel ..."><img alt="Comparison of kernel ridge regression and SVR" src="../../_images/sphx_glr_plot_kernel_ridge_regression_thumb.png" />
<p><a class="reference internal" href="plot_kernel_ridge_regression.html#sphx-glr-auto-examples-miscellaneous-plot-kernel-ridge-regression-py"><span class="std std-ref">Comparison of kernel ridge regression and SVR</span></a></p>
<div class="sphx-glr-thumbnail-title">Comparison of kernel ridge regression and SVR</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="The default configuration for displaying a pipeline in a Jupyter Notebook is 'diagram' where se..."><img alt="Displaying Pipelines" src="../../_images/sphx_glr_plot_pipeline_display_thumb.png" />
<p><a class="reference internal" href="plot_pipeline_display.html#sphx-glr-auto-examples-miscellaneous-plot-pipeline-display-py"><span class="std std-ref">Displaying Pipelines</span></a></p>
<div class="sphx-glr-thumbnail-title">Displaying Pipelines</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example illustrates different ways estimators and pipelines can be displayed."><img alt="Displaying estimators and complex pipelines" src="../../_images/sphx_glr_plot_estimator_representation_thumb.png" />
<p><a class="reference internal" href="plot_estimator_representation.html#sphx-glr-auto-examples-miscellaneous-plot-estimator-representation-py"><span class="std std-ref">Displaying estimators and complex pipelines</span></a></p>
<div class="sphx-glr-thumbnail-title">Displaying estimators and complex pipelines</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example benchmarks outlier detection algorithms, local_outlier_factor (LOF) and isolation_..."><img alt="Evaluation of outlier detection estimators" src="../../_images/sphx_glr_plot_outlier_detection_bench_thumb.png" />
<p><a class="reference internal" href="plot_outlier_detection_bench.html#sphx-glr-auto-examples-miscellaneous-plot-outlier-detection-bench-py"><span class="std std-ref">Evaluation of outlier detection estimators</span></a></p>
<div class="sphx-glr-thumbnail-title">Evaluation of outlier detection estimators</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="An example illustrating the approximation of the feature map of an RBF kernel."><img alt="Explicit feature map approximation for RBF kernels" src="../../_images/sphx_glr_plot_kernel_approximation_thumb.png" />
<p><a class="reference internal" href="plot_kernel_approximation.html#sphx-glr-auto-examples-miscellaneous-plot-kernel-approximation-py"><span class="std std-ref">Explicit feature map approximation for RBF kernels</span></a></p>
<div class="sphx-glr-thumbnail-title">Explicit feature map approximation for RBF kernels</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example shows the use of multi-output estimator to complete images. The goal is to predict..."><img alt="Face completion with a multi-output estimators" src="../../_images/sphx_glr_plot_multioutput_face_completion_thumb.png" />
<p><a class="reference internal" href="plot_multioutput_face_completion.html#sphx-glr-auto-examples-miscellaneous-plot-multioutput-face-completion-py"><span class="std std-ref">Face completion with a multi-output estimators</span></a></p>
<div class="sphx-glr-thumbnail-title">Face completion with a multi-output estimators</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example will demonstrate the set_output API to configure transformers to output pandas Dat..."><img alt="Introducing the `set_output` API" src="../../_images/sphx_glr_plot_set_output_thumb.png" />
<p><a class="reference internal" href="plot_set_output.html#sphx-glr-auto-examples-miscellaneous-plot-set-output-py"><span class="std std-ref">Introducing the set_output API</span></a></p>
<div class="sphx-glr-thumbnail-title">Introducing the `set_output` API</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="An illustration of the isotonic regression on generated data (non-linear monotonic trend with h..."><img alt="Isotonic Regression" src="../../_images/sphx_glr_plot_isotonic_regression_thumb.png" />
<p><a class="reference internal" href="plot_isotonic_regression.html#sphx-glr-auto-examples-miscellaneous-plot-isotonic-regression-py"><span class="std std-ref">Isotonic Regression</span></a></p>
<div class="sphx-glr-thumbnail-title">Isotonic Regression</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="This example simulates a multi-label document classification problem. The dataset is generated ..."><img alt="Multilabel classification" src="../../_images/sphx_glr_plot_multilabel_thumb.png" />
<p><a class="reference internal" href="plot_multilabel.html#sphx-glr-auto-examples-miscellaneous-plot-multilabel-py"><span class="std std-ref">Multilabel classification</span></a></p>
<div class="sphx-glr-thumbnail-title">Multilabel classification</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="ROC Curve with Visualization API"><img alt="ROC Curve with Visualization API" src="../../_images/sphx_glr_plot_roc_curve_visualization_api_thumb.png" />
<p><a class="reference internal" href="plot_roc_curve_visualization_api.html#sphx-glr-auto-examples-miscellaneous-plot-roc-curve-visualization-api-py"><span class="std std-ref">ROC Curve with Visualization API</span></a></p>
<div class="sphx-glr-thumbnail-title">ROC Curve with Visualization API</div>
</div><div class="sphx-glr-thumbcontainer" tooltip=" The `Johnson-Lindenstrauss lemma`_ states that any high dimensional dataset can be randomly pr..."><img alt="The Johnson-Lindenstrauss bound for embedding with random projections" src="../../_images/sphx_glr_plot_johnson_lindenstrauss_bound_thumb.png" />
<p><a class="reference internal" href="plot_johnson_lindenstrauss_bound.html#sphx-glr-auto-examples-miscellaneous-plot-johnson-lindenstrauss-bound-py"><span class="std std-ref">The Johnson-Lindenstrauss bound for embedding with random projections</span></a></p>
<div class="sphx-glr-thumbnail-title">The Johnson-Lindenstrauss bound for embedding with random projections</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="In this example, we will construct display objects, ConfusionMatrixDisplay, RocCurveDisplay, an..."><img alt="Visualizations with Display Objects" src="../../_images/sphx_glr_plot_display_object_visualization_thumb.png" />
<p><a class="reference internal" href="plot_display_object_visualization.html#sphx-glr-auto-examples-miscellaneous-plot-display-object-visualization-py"><span class="std std-ref">Visualizations with Display Objects</span></a></p>
<div class="sphx-glr-thumbnail-title">Visualizations with Display Objects</div>
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