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LabelEncoder — scikit-learn 1.8.0 documen...
array([1, 2, 6]) >>> le . transform ([ 1 , 1 , 2 , 6...inverse_transform ([ 0 , 0 , 1 , 2 ]) array([1, 1, 2, 6]) It can also be used...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html -
ClassifierMixin — scikit-learn 1.8.0 docu...
predict ( X ) array([1, 1, 1]) >>> estimator ....MyEstimator ( param = 1 ) >>> X = np . array ([[ 1 , 2 ], [ 2 ,...scikit-learn.org/stable/modules/generated/sklearn.base.ClassifierMixin.html -
StratifiedShuffleSplit — scikit-learn 1.8...
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [...np . array ([ 0 , 0 , 0 , 1 , 1 , 1 ]) >>> sss = StratifiedShuffleSpl...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html -
OAS — scikit-learn 1.8.0 documentation
precision_ array([[ 1.7833, -1.2431 ], [-1.2431, 3.3889]]) >>>...the estimator. References [ 1 ] ( 1 , 2 ) “Shrinkage algorithms...scikit-learn.org/stable/modules/generated/sklearn.covariance.OAS.html -
PowerTransformer — scikit-learn 1.8.0 doc...
data )) [[-1.316 -0.707] [ 0.209 -0.707] [ 1.106 1.414]] fit (...= ( X * lambda_ + 1 ) ** ( 1 / lambda_ ) - 1 elif X < 0 and...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
d2_tweedie_score — scikit-learn 1.8.0 doc...
1 , 2.5 , 7 ] >>> y_pred = [ 1 , 1 , 5 , 3.5...explained. Best possible score is 1.0 and it can be negative (because...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_tweedie_score.html -
OrdinalEncoder — scikit-learn 1.8.0 docum...
inverse_transform ([[ 1 , 0 ], [ 0 , 1 ]]) array([['Male', 1], ['Female',... =- 1 ) . fit_transform ( X ) array([[ 1., 0.], [ 0., 1.], [...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
laplacian_kernel — scikit-learn 1.8.0 doc...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...default=None If None, defaults to 1.0 / n_features. Otherwise it should...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.laplacian_kernel.html -
rbf_kernel — scikit-learn 1.8.0 documenta...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...default=None If None, defaults to 1.0 / n_features. Returns : kernel...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.rbf_kernel.html -
load_svmlight_files — scikit-learn 1.8.0 ...
shape[1] == X_test.shape[1]). This may not be the...query_id=False , offset=0 , length=-1 ) [source] # Load dataset from...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_svmlight_files.html