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average_precision_score — scikit-learn 1.8.0 do...
1 , 1 ]) >>> y_scores = np . array ([ 0.1 , 0.4 , 0.35..., 0.1 ], ... [ 0.4 , 0.3 , 0.3 ], ... [ 0.1 , 0.8 , 0.1 ], ......scikit-learn.org/stable/modules/generated/sklearn.metrics.average_precision_score.html -
LogisticRegressionCV — scikit-learn 1.8.0 docum...
l1_ratio = 1 it is an L1 penalty. For 0 < l1_ratio < 1 , the penalty...since version 1.8: l1_ratios=None is deprecated in 1.8 and will...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
OutlierMixin — scikit-learn 1.8.0 documentation
fit_predict ( X ) array([1., 1., 1.]) fit_predict ( X , y = None...labels for X. Returns -1 for outliers and 1 for inliers. Parameters...scikit-learn.org/stable/modules/generated/sklearn.base.OutlierMixin.html -
DecisionTreeClassifier — scikit-learn 1.8.0 doc...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}]. The “balanced” mode uses...scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html -
KDTree — scikit-learn 1.8.0 documentation
query ( X [: 1 ], k = 3 ) >>> print ( ind ) #...indices of 3 closest neighbors [0 3 1] >>> print ( dist ) # distances...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html -
pairwise_distances_argmin — scikit-learn 1.8.0 ...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances_argmin.html -
LeavePGroupsOut — scikit-learn 1.8.0 documentation
Test: index=[0 1], group=[1 2] Fold 1: Train: index=[1], group=[2]...array ([ 1 , 2 , 1 ]) >>> groups = np . array ([ 1 , 2 , 3 ])...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePGroupsOut.html -
normalize — scikit-learn 1.8.0 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> normalize (...if axis is 0). axis {0, 1}, default=1 Define axis used to normalize...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html -
KBinsDiscretizer — scikit-learn 1.8.0 documenta...
[ 1., 1., 1., 0.], [ 2., 2., 2., 1.], [ 2., 2., 2.,...>>> X = [[ - 2 , 1 , - 4 , - 1 ], ... [ - 1 , 2 , - 3 , - 0.5...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html -
NearestCentroid — scikit-learn 1.8.0 documentation
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestCentroid.html