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KNeighborsClassifier — scikit-learn 1.7.2 docum...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...bors=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1. ]]))...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html -
KNeighborsRegressor — scikit-learn 1.7.2 docume...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...bors=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1. ]]))...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
OPTICS — scikit-learn 1.7.2 documentation
1, 1, 1]) For a more detailed example...min_samples int > 1 or float between 0 and 1, default=5 The number...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
SGDClassifier — scikit-learn 1.7.2 documentation
array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...(clip(decision_function(X), -1, 1) + 1) / 2. For other loss functions...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html -
DecisionTreeClassifier — scikit-learn 1.7.2 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 -
KBinsDiscretizer — scikit-learn 1.7.2 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 1.7.2 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 -
NuSVR — scikit-learn 1.7.2 documentation
Added in version 1.1. n_support_ ndarray of shape (1,), dtype=int32...(0, 1]. By default 0.5 will be taken. C float, default=1.0 Penalty...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html -
PolynomialCountSketch — scikit-learn 1.7.2 docu...
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...Array with random entries in {+1, -1}, used to represent the 2-wise...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.PolynomialCountSketch.html -
AffinityPropagation — scikit-learn 1.7.2 docume...
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2.... labels_ array([0, 0, 0, 1, 1, 1]) >>> clustering . predict...scikit-learn.org/stable/modules/generated/sklearn.cluster.AffinityPropagation.html