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PowerTransformer — scikit-learn 1.7.0 documenta...
2 ], [ 3 , 2 ], [ 4 , 5 ]] >>> print...0 and lambda_ != 2 : X_original = 1 - ( - ( 2 - lambda_ ) * X...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
MultiTaskLasso — scikit-learn 1.7.0 documentation
2 ], [ 2 , 4 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 3 ]]) ...it is: 1 / ( 2 * n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html -
lasso_path — scikit-learn 1.7.0 documentation
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...it is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html -
CCA — scikit-learn 1.7.0 documentation
[ 2. , 2. , 2. ], [ 3. , 5. , 4. ]] >>>...y = [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 ,...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html -
DecisionTreeRegressor — scikit-learn 1.7.0 docu...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...= None , min_samples_split = 2 , min_samples_leaf = 1 , min_...scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html -
make_moons — scikit-learn 1.7.0 documentation
2 , random_state = 42 ) >>> X . shape (200, 2) >>> y ....n_samples int or tuple of shape (2,), dtype=int, default=100 If int,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html -
mutual_info_regression — scikit-learn 1.7.0 doc...
[ 2 ] ( 1 , 2 ) A. Kraskov, H. Stogbauer...neighbors distances as described in [2] and [3] . Both methods are based...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.mutual_info_regression.html -
VotingRegressor — scikit-learn 1.7.0 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...X = np . array ([[ 1 , 1 ], [ 2 , 4 ], [ 3 , 9 ], [ 4 , 16 ],...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingRegressor.html -
RobustScaler — scikit-learn 1.7.0 documentation
- 2. , 2. ], ... [ - 2. , 1. , 3. ], ... [ 4. , 1. , - 2. ]]...transform ( X ) array([[ 0. , -2. , 0. ], [-1. , 0. , 0.4], [ 1....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html -
TweedieRegressor — scikit-learn 1.7.0 documenta...
2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3 ]] >>> y = [ 2 , 3.5...determination R^2. R^2 uses squared error and D^2 uses the deviance...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TweedieRegressor.html