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KMeans — scikit-learn 1.7.0 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Clustering...X = np . array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2...scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html -
Developing scikit-learn estimators — scikit-lea...
SGDClassifier ([[ 1 , 2 ], [ 2 , 3 ]], [ - 1 , 1 ]) # WRONG! Ideally,...be modified if param1 > 1 : param2 += 1 self . param1 = param1...scikit-learn.org/stable/developers/develop.html -
jaccard_score — scikit-learn 1.7.0 documentation
1 , 1 ], ... [ 1 , 1 , 0 ]]) >>> y_pred =...= np . array ([[ 1 , 1 , 1 ], ... [ 1 , 0 , 0 ]]) In the binary...scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_score.html -
precision_score — scikit-learn 1.7.0 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 1.7.0 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 1.7.0 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 -
kneighbors_graph — scikit-learn 1.7.0 documenta...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) Gallery...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.neighbors.kneighbors_graph.html -
ValidationCurveDisplay — scikit-learn 1.7.0 doc...
means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn 1.3 Release Highlights for scikit-learn 1.3 On this...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ValidationCurveDisplay.html -
RidgeCV — scikit-learn 1.7.0 documentation
1, 1.0, 10.0) , * , fit_intercept...shape (n_alphas,), default=(0.1, 1.0, 10.0) Array of alpha values...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html -
confusion_matrix — scikit-learn 1.7.0 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