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scikit-learn 1.3.2
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# Computation times

00:18.069 total execution time for auto_examples_svm files:

Scaling the regularization parameter for SVCs (`plot_svm_scale_c.py`) | 00:10.703 | 0.0 MB
RBF SVM parameters (`plot_rbf_parameters.py`) | 00:03.552 | 0.0 MB
Non-linear SVM (`plot_svm_nonlinear.py`) | 00:01.188 | 0.0 MB
SVM Tie Breaking Example (`plot_svm_tie_breaking.py`) | 00:00.661 | 0.0 MB
SVM: Weighted samples (`plot_weighted_samples.py`) | 00:00.368 | 0.0 MB
Support Vector Regression (SVR) using linear and non-linear kernels (`plot_svm_regression.py`) | 00:00.313 | 0.0 MB
Plot classification boundaries with different SVM Kernels (`plot_svm_kernels.py`) | 00:00.280 | 0.0 MB
One-class SVM with non-linear kernel (RBF) (`plot_oneclass.py`) | 00:00.265 | 0.0 MB
SVM-Anova: SVM with univariate feature selection (`plot_svm_anova.py`) | 00:00.194 | 0.0 MB
Plot different SVM classifiers in the iris dataset (`plot_iris_svc.py`) | 00:00.136 | 0.0 MB
Plot the support vectors in LinearSVC (`plot_linearsvc_support_vectors.py`) | 00:00.123 | 0.0 MB
SVM: Separating hyperplane for unbalanced classes (`plot_separating_hyperplane_unbalanced.py`) | 00:00.115 | 0.0 MB
SVM with custom kernel (`plot_custom_kernel.py`) | 00:00.079 | 0.0 MB
SVM Margins Example (`plot_svm_margin.py`) | 00:00.048 | 0.0 MB
SVM: Maximum margin separating hyperplane (`plot_separating_hyperplane.py`) | 00:00.046 | 0.0 MB