- Sort Score
- Num 10 results
- Language All
- Labels All
Results 71 - 80 of over 10,000 for 1 (0.1 seconds)
-
cluster_optics_xi — scikit-learn 1.8.0 do...
1, 1, 1]) >>> clusters array([[0,...min_samples int > 1 or float between 0 and 1 The same as the min_samples...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.html -
VotingClassifier — scikit-learn 1.8.0 doc...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html -
SparseCoder — scikit-learn 1.8.0 document...
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.decomposition.SparseCoder.html -
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 -
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