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HDBSCAN — scikit-learn 1.7.2 documentation
inf) are given the label -2. Samples with missing data are...clusters. That is to say, the -1, -2, -3 labels for the outlier clusters...scikit-learn.org/stable/modules/generated/sklearn.cluster.HDBSCAN.html -
MaxAbsScaler — scikit-learn 1.7.2 documentation
2. ], ... [ 2. , 0. , 0. ], ... [ 0. ,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
MeanShift — scikit-learn 1.7.2 documentation
complexity will tend towards O(T*n^2). Scalability can be boosted by...X = np . array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html -
LogisticRegressionCV — scikit-learn 1.7.2 docum...
[: 2 , :]) array([0, 0]) >>> clf . predict_proba ( X [: 2 , :])...SAGA solver. Added in version 1.2: newton-cholesky solver. Multinomial...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
accuracy_score — scikit-learn 1.7.2 documentation
2 , 1 , 3 ] >>> y_true = [ 0 , 1 , 2 , 3 ] >>> accuracy_score...], [ 1 , 1 ]]), np . ones (( 2 , 2 ))) 0.5 Gallery examples # Plot...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html -
LogisticRegression — scikit-learn 1.7.2 documen...
[: 2 , :]) array([0, 0]) >>> clf . predict_proba ( X [: 2 , :])...‘lbfgs’ in 0.22. Added in version 1.2: newton-cholesky solver. Multinomial...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html -
StratifiedGroupKFold — scikit-learn 1.7.2 docum...
index=[ 0 1 2 3 15 16] group=[1 1 2 2 8 8] Fold 2: Train: index=[...index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5 8...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
MultinomialNB — scikit-learn 1.7.2 documentation
2. Changed in version 1.4: The default...)) >>> y = np . array ([ 1 , 2 , 3 , 4 , 5 , 6 ]) >>> from sklearn.naive_bayes...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html -
KMeans — scikit-learn 1.7.2 documentation
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...cluster_centers_ array([[10., 2.], [ 1., 2.]]) For examples of common...scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html -
shuffle — scikit-learn 1.7.2 documentation
2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html