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sklearn.naive_bayes.GaussianNB — scikit-learn 1...
classification on an array of test vectors X. predict_joint_log_proba...probability estimates for the test vector X. predict_log_proba...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
sklearn.multiclass.OneVsOneClassifier — scikit-...
X_test , y_train , y_test = train_test_split ( ......sklearn.model_selection import train_test_split >>> from sklearn.multiclass...scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsOneClassifier.html -
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 -
sklearn.naive_bayes.BernoulliNB — scikit-learn ...
classification on an array of test vectors X. predict_joint_log_proba...probability estimates for the test vector X. predict_log_proba...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html -
Supervised learning: predicting an output varia...
iris_X_test = iris_X [ indices [ - 10 :]] >>> iris_y_test = iris_y...predict ( diabetes_X_test ) - diabetes_y_test ) ** 2 ) 2004.5......scikit-learn.org/stable/tutorial/statistical_inference/supervised_learning.html -
sklearn.covariance.GraphicalLassoCV — scikit-le...
score (X_test[, y]) Compute the log-likelihood of X_test under the...: X_test array-like of shape (n_samples, n_features) Test data...scikit-learn.org/stable/modules/generated/sklearn.covariance.GraphicalLassoCV.html -
sklearn.datasets.fetch_species_distributions — ...
scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.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 -
feature_selection.rst.txt
the best features based on univariate statistical tests. It can...we can use a F-test to retrieve the two best features for a dataset...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
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