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sklearn.preprocessing.quantile_transform — scik...
splitting into training and test sets. This will bias the model...information would have leaked from the test set to the training set. In...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.quantile_transform.html -
sklearn.discriminant_analysis.LinearDiscriminan...
the mean accuracy on the given test data and labels. set_output...n_features) Array of samples (test vectors). Returns : C ndarray...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysi... -
Examples — scikit-learn 1.4.2 documentation
(ROC) Nested versus non-nested cross-validation Nested versus...Comparison of F-test and mutual information Comparison of F-test and mutual...scikit-learn.org/stable/auto_examples/index.html -
Movie search application | Elastic
www.elastic.co/demo-gallery/ent-search -
sklearn.semi_supervised.LabelSpreading — scikit...
on a Text Dataset Semi-supervised Classification on a Text Dataset...the mean accuracy on the given test data and labels. set_params...scikit-learn.org/stable/modules/generated/sklearn.semi_supervised.LabelSpreading.html -
sklearn.dummy.DummyRegressor — scikit-learn 1.4...
n_features) Test samples. Passing None as test samples gives...return_std]) Perform classification on test vectors X. score (X, y[, sample_weight])...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyRegressor.html -
sklearn.linear_model.RidgeCV — scikit-learn 1.4...
test) splits as arrays of indices....shape (n_samples, n_features) Test samples. For some estimators...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html -
Relevance workbench | Elastic
www.elastic.co/demo-gallery/relevance-workbench -
sklearn.linear_model.ElasticNet — scikit-learn ...
Train error vs Test error Train error vs Test error...shape (n_samples, n_features) Test samples. For some estimators...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
plot_multi_metric_evaluation.rst.txt
1)[0][0] best_score = results["mean_test_%s" % scorer][best_index]...etc...) The ``best_estimator_``, ``best_index_``, ``best_score_``...scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt