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| .. | ||
| cluster | ||
| gaussian_process | ||
| linear_model | ||
| mixture | ||
| sgd | ||
| svm | ||
| README.txt | ||
| document_classification_20newsgroups.py | ||
| feature_selection_pipeline.py | ||
| grid_search_digits.py | ||
| grid_search_text_feature_extraction.py | ||
| logistic_l1_l2_coef.py | ||
| mlcomp_sparse_document_classification.py | ||
| naive_bayes.py | ||
| plot_classification_probability.py | ||
| plot_confusion_matrix.py | ||
| plot_covariance_estimation.py | ||
| plot_digits_classification.py | ||
| plot_face_recognition.py | ||
| plot_feature_selection.py | ||
| plot_ica_blind_source_separation.py | ||
| plot_ica_vs_pca.py | ||
| plot_lda_qda.py | ||
| plot_lda_vs_qda.py | ||
| plot_neighbors.py | ||
| plot_pca.py | ||
| plot_precision_recall.py | ||
| plot_rfe_digits.py | ||
| plot_rfe_with_cross_validation.py | ||
| plot_roc.py | ||
| plot_roc_crossval.py | ||
| plot_species_distribution_modeling.py | ||
| plot_train_error_vs_test_error.py | ||
| stock_market.py | ||
README.txt
General examples ------------------- General-purpose and introductory examples for the scikit.