.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/svm/plot_separating_hyperplane.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code or to run this example in your browser via JupyterLite or Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_svm_plot_separating_hyperplane.py: ========================================= SVM: Maximum margin separating hyperplane ========================================= Plot the maximum margin separating hyperplane within a two-class separable dataset using a Support Vector Machine classifier with linear kernel. .. GENERATED FROM PYTHON SOURCE LINES 11-49 .. image-sg:: /auto_examples/svm/images/sphx_glr_plot_separating_hyperplane_001.png :alt: plot separating hyperplane :srcset: /auto_examples/svm/images/sphx_glr_plot_separating_hyperplane_001.png :class: sphx-glr-single-img .. code-block:: Python import matplotlib.pyplot as plt from sklearn import svm from sklearn.datasets import make_blobs from sklearn.inspection import DecisionBoundaryDisplay # we create 40 separable points X, y = make_blobs(n_samples=40, centers=2, random_state=6) # fit the model, don't regularize for illustration purposes clf = svm.SVC(kernel="linear", C=1000) clf.fit(X, y) plt.scatter(X[:, 0], X[:, 1], c=y, s=30, cmap=plt.cm.Paired) # plot the decision function ax = plt.gca() DecisionBoundaryDisplay.from_estimator( clf, X, plot_method="contour", colors="k", levels=[-1, 0, 1], alpha=0.5, linestyles=["--", "-", "--"], ax=ax, ) # plot support vectors ax.scatter( clf.support_vectors_[:, 0], clf.support_vectors_[:, 1], s=100, linewidth=1, facecolors="none", edgecolors="k", ) plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.070 seconds) .. _sphx_glr_download_auto_examples_svm_plot_separating_hyperplane.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/scikit-learn/scikit-learn/1.4.X?urlpath=lab/tree/notebooks/auto_examples/svm/plot_separating_hyperplane.ipynb :alt: Launch binder :width: 150 px .. container:: lite-badge .. image:: images/jupyterlite_badge_logo.svg :target: ../../lite/lab/?path=auto_examples/svm/plot_separating_hyperplane.ipynb :alt: Launch JupyterLite :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_separating_hyperplane.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_separating_hyperplane.py ` .. include:: plot_separating_hyperplane.recommendations .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_