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jaccard_score — scikit-learn 1.7.2 documentation
y_true = np . array ([[ 0 , 1 , 1 ], ... [ 1 , 1 , 0 ]]) >>> y_pred...y_pred = np . array ([[ 1 , 1 , 1 ], ... [ 1 , 0 , 0 ]]) In the binary...scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_score.html -
GaussianMixture — scikit-learn 1.7.2 documentation
covariance_type {‘full’, ‘tied’, ‘diag’, ‘spherical’}, default=’full’ String...‘k-means++’, ‘random’, ‘random_from_data’}, default=’kmeans’ The method...scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html -
LocallyLinearEmbedding — scikit-learn 1.7.2 doc...
{‘standard’, ‘hessian’, ‘modified’, ‘ltsa’}, default=’standard’ standard...distances. eigen_solver {‘auto’, ‘arpack’, ‘dense’}, default=’auto’...scikit-learn.org/stable/modules/generated/sklearn.manifold.LocallyLinearEmbedding.html -
BaggingRegressor — scikit-learn 1.7.2 documenta...
n_estimators = 10 , * , max_samples = 1.0 , max_features = 1.0 , bootstrap...databases and on-line”, Machine Learning, 36(1), 85-103, 1999. [ 2 ] L....scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
mean_squared_error — scikit-learn 1.7.2 documen...
1 , 1 ],[ 7 , - 6 ]] >>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8...y_pred , multioutput = [ 0.3 , 0.7 ]) 0.825... Gallery examples # Model...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html -
hinge_loss — scikit-learn 1.7.2 documentation
array([-2.18, 2.36, 0.09]) >>> hinge_loss ([ - 1 , 1 , 1 ], pred_decision...array ([ 0 , 1 , 2 , 3 ]) >>> labels = np . array ([ 0 , 1 , 2 , 3...scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html -
mean_absolute_error — scikit-learn 1.7.2 docume...
= [ 3 , - 0.5 , 2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>..., 1 ], [ 7 , - 6 ]] >>> y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html -
auc — scikit-learn 1.7.2 documentation
0.1 , 0.4 , 0.35 , 0.8 ]) >>> fpr , tpr , thresholds = metrics...np . array ([ 1 , 1 , 2 , 2 ]) >>> y_score = np . array ([ 0.1...scikit-learn.org/stable/modules/generated/sklearn.metrics.auc.html -
DecisionBoundaryDisplay — scikit-learn 1.7.2 do...
max ()), ... np . linspace ( iris . data [:, 1 ] . min (), iris...iris . data [:, 1 ] . max ()) ... ) >>> grid = np . vstack ([ feature_1...scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html -
plot_classifier_comparison.rst.txt
KNeighborsClassifier(3), SVC(kernel="linear", C=0.025, random_state=42), SVC(gamma=2,...Process", "Decision Tree", "Random Forest", "Neural Net", "AdaBoost",...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt