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RandomTreesEmbedding — scikit-learn 1.6.1 docum...
1.], [1., 0., 1., 0., 1., 0., 1., 0., 1., 0.], [0., 1., 1.,...array([[0., 1., 1., 0., 1., 0., 0., 1., 1., 0.], [0., 1., 1., 0., 1.,...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomTreesEmbedding.html -
StratifiedGroupKFold — scikit-learn 1.6.1 docum...
1 , 1 , 1 , 1 , 1 , 1 , 0 , 0 , 0 , 0 , 0...Train: index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
shuffle — scikit-learn 1.6.1 documentation
1.], [1., 0.]]) >>> y array([2, 1, 0]) >>> shuffle...>>> X = np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
OneClassSVM — scikit-learn 1.6.1 documentation
predict ( X ) array([-1, 1, 1, 1, -1]) >>> clf . score_samples...default=-1 Hard limit on iterations within solver, or -1 for no...scikit-learn.org/stable/modules/generated/sklearn.svm.OneClassSVM.html -
OneHotEncoder — scikit-learn 1.6.1 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...'Female' , 1 ], [ 'Male' , 4 ]]) . toarray () array([[1., 0., 1., 0.,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html -
SVC — scikit-learn 1.6.1 documentation
array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...default=-1 Hard limit on iterations within solver, or -1 for no...scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html -
KNeighborsTransformer — scikit-learn 1.6.1 docu...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) set_output...bors=1) >>> print ( neigh . kneighbors ([[ 1. , 1. , 1. ]]))...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html -
ExtraTreesClassifier — scikit-learn 1.6.1 docum...
[{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.ensemble.ExtraTreesClassifier.html -
Hyperparameter — scikit-learn 1.6.1 documentation
n_elements = 1 , fixed = None ) [source] # A...the parameter. If n_elements>1, a pair of 1d array with n_elements...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Hyperparameter.html -
RandomForestClassifier — scikit-learn 1.6.1 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.ensemble.RandomForestClassifier.html