![]() ![]() plot_linear_regression: A quick way for plotting linear regression fits.plot_learning_curves: Plot learning curves from training and test sets.plot_decision_regions: Visualize the decision regions of a classifier.plot_confusion_matrix: Visualize confusion matrices.heatmap: Create a heatmap in matplotlib.enrichment_plot: create an enrichment plot for cumulative counts.ecdf: Create an empirical cumulative distribution function plot.plot_pca_correlation_graph: plot correlations between original features and principal components.checkerboard_plot: Create a checkerboard plot in matplotlib.Scategory_scatter: Create a scatterplot with categories in different colors.vectorspace_orthonormalization: Converts a set of linearly independent vectors to a set of orthonormal basis vectors.vectorspace_dimensionality: compute the number of dimensions that a set of vectors spans.num_permutations: number of permutations for creating subsequences of *k* elements.num_combinations: combinations for creating subsequences of *k* elements.EyepadAlign: align face images based on eye location.extract_face_landmarks: extract 68 landmark features from face images.find_files: Find files based on substring matches.find_filegroups: Find files that only differ via their file extensions.SequentialFeatureSelector: The popular forward and backward feature selection approaches (including floating variants).ExhaustiveFeatureSelector: Optimal feature sets by considering all possible feature combinations.ColumnSelector: Scikit-learn utility function to select specific columns in a pipeline.PrincipalComponentAnalysis: Principal component analysis (PCA) for dimensionality reduction.LinearDiscriminantAnalysis: Linear discriminant analysis for dimensionality reduction.scoring: computing various performance metrics.RandomHoldoutSplit: split a dataset into a train and validation subset for validation. ![]() PredefinedHoldoutSplit: Utility for the holdout method compatible with scikit-learn.permutation_test: Permutation test for hypothesis testing.paired_ttest_resample: Resampled paired *t* test.paired_ttest_kfold_cv: K-fold cross-validated paired *t* test.paired_ttest_5x2cv: 5x2cv paired *t* test for classifier comparisons.mcnemar: McNemar's test for classifier comparisons. ![]()
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