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precision_score — scikit-learn 1.5.0 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> precision_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html -
completeness_score — scikit-learn 1.5.0 documen...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect labelings...completeness_score ([ 0 , 0 , 1 , 1 ], [ 0 , 1 , 0 , 1 ])) 0.0 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.completeness_score.html -
f1_score — scikit-learn 1.5.0 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> f1_score ( y_true...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html -
confusion_matrix — scikit-learn 1.5.0 documenta...
1 , 0 , 1 ], [ 1 , 1 , 1 , 0 ]) . ravel ()...negatives is \(C_{1,0}\) , true positives is \(C_{1,1}\) and false...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
minmax_scale — scikit-learn 1.5.0 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> minmax_scale...independently array([[0., 1., 1.], [1., 0., 0.]]) >>> minmax_scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.minmax_scale.html -
estimate_bandwidth — scikit-learn 1.5.0 documen...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.cluster.estimate_bandwidth.html -
hamming_loss — scikit-learn 1.5.0 documentation
1 ], [ 1 , 1 ]]), np . zeros (( 2 , 2...between 0 and 1, lower being better. References [ 1 ] Grigorios...scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html -
ValidationCurveDisplay — scikit-learn 1.5.0 doc...
means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn 1.3 Release Highlights for scikit-learn 1.3 Plotting...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ValidationCurveDisplay.html -
accuracy_score — scikit-learn 1.5.0 documentation
1 ], [ 1 , 1 ]]), np . ones (( 2 , 2...y_pred = [ 0 , 2 , 1 , 3 ] >>> y_true = [ 0 , 1 , 2 , 3 ] >>> accuracy_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html -
fetch_20newsgroups — scikit-learn 1.5.0 documen...
1, 1, 1, 0, 1, 1, 0, 0, 0]) Gallery examples...Added in version 1.5. delay float, default=1.0 Number of seconds...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups.html