- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 781 - 790 of 2,914 for 1 (0.12 sec)
-
RBFSampler — scikit-learn 1.7.0 documentation
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...in version 1.2: The option "scale" was added in 1.2. n_components...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.RBFSampler.html -
GradientBoostingRegressor — scikit-learn 1.7.0 ...
1 , n_estimators = 100 , subsample = 1.0 , criterion...in the range [1, inf) . subsample float, default=1.0 The fraction...scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingRegressor.html -
Regularization path of L1- Logistic Regression ...
1 , 16 ) Create a pipeline with...i in range ( coefs_ . shape [ 1 ]): plt . semilogx ( cs , coefs_...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_path.html -
MultiTaskElasticNetCV — scikit-learn 1.7.0 docu...
[ 1 , 1 ], [ 2 , 2 ]], ... [[ 0 , 0 ], [ 1 , 1 ], [ 2 ,...with 0 < l1_ratio <= 1. For l1_ratio = 1 the penalty is an L1/L2...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskElasticNetCV.html -
SVR — scikit-learn 1.7.0 documentation
Added in version 1.1. n_support_ ndarray of shape (1,), dtype=int32..., tol = 0.001 , C = 1.0 , epsilon = 0.1 , shrinking = True ,...scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html -
LeaveOneGroupOut — scikit-learn 1.7.0 documenta...
index=[0 1], group=[1 1] Fold 1: Train: index=[0 1], group=[1 1] Test:...array ([ 1 , 2 , 1 , 2 ]) >>> groups = np . array ([ 1 , 1 , 2 ,...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeaveOneGroupOut.html -
PolynomialFeatures — scikit-learn 1.7.0 documen...
fit_transform ( X ) array([[ 1., 0., 1., 0., 0., 1.], [ 1., 2., 3., 4., 6.,...) array([[ 1., 0., 1., 0.], [ 1., 2., 3., 6.], [ 1., 4., 5., 20.]])...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html -
label_ranking_loss — scikit-learn 1.7.0 documen...
1 ], [ 1 , 0.2 , 0.1 ]] >>> label_ranking_loss...label_ranking_loss >>> y_true = [[ 1 , 0 , 0 ], [ 0 , 0 , 1 ]] >>> y_score = [[...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_loss.html -
MultiTaskElasticNet — scikit-learn 1.7.0 docume...
1 ) >>> clf . fit ([[ 0 , 0 ], [ 1 , 1 ], [ 2 , 2...], [ 1 , 1 ], [ 2 , 2 ]]) MultiTaskElasticNet(alpha=0.1) >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskElasticNet.html -
SelectFromModel — scikit-learn 1.7.0 documentation
[ - 1.34 , - 0.48 , - 2.55 ], ... [ 1.92 , 1.48 , 0.65...version 0.20. Changed in version 1.1: max_features accepts a callable....scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFromModel.html