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index.rst.txt
example compares non-nested and nested cross-validation strategies...class="sphx-glr-thumbnail-title">Nested versus non-nested cross-validation</div>...scikit-learn.org/stable/_sources/auto_examples/index.rst.txt -
contributing.rst.txt
sklearn/linear_model/tests/test_logistic.py` to run the tests specific to...center .. _testing_coverage: Testing and improving test coverage...scikit-learn.org/dev/_sources/developers/contributing.rst.txt -
linear_model.rst.txt
cost of :math:`O(n_{\text{samples}} n_{\text{features}}^2)`, assuming...that :math:`n_{\text{samples}} \geq n_{\text{features}}`. .....scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
plot_classifier_comparison.rst.txt
and test part X, y = ds X_train, X_test, y_train, y_test = train_test_split(...Plot the testing points ax.scatter( X_test[:, 0], X_test[:, 1],...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt -
about.rst.txt
div:: sk-text-image-grid-small .. div:: text-box `:probabl...... div:: sk-text-image-grid-small .. div:: text-box The `Members...scikit-learn.org/stable/_sources/about.rst.txt -
support.rst.txt
about repository updates and test failures on the `scikit-learn-commits...scikit-learn.org/stable/_sources/support.rst.txt -
preprocessing.rst.txt
K_{test} - 1'_{\text{n}_{samples}} K - K_{test} 1_{\text{n}_{samples}}...>>> X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
plot_release_highlights_1_4_0.rst.txt
X_test, y_train, y_test = train_test_split(X_adult,...n(X_test) print(f"ROC AUC score is {roc_auc_score(y_test, y_decision)}")...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
classes.rst.txt
_text_feature_extraction_ref: From text --------- .....feature_extraction.text.CountVectorizer feature_extraction.text.HashingVectorizer...scikit-learn.org/stable/_sources/modules/classes.rst.txt -
feature_extraction.rst.txt
:math:`\text{tf-idf}_{\text{term1}} = \text{tf} \times \text{idf}...:math:`\text{tf-idf(t,d)}=\text{tf(t,d)} \times \text{idf(t)}`....scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt