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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 -
mean_poisson_deviance — scikit-learn 1.7.0 docu...
y_true = [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2. ] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html -
MLPRegressor — scikit-learn 1.7.0 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...validation_fraction = 0.1 , beta_1 = 0.9 , beta_2 = 0.999 , epsilon = 1e-08 , n_iter_no_change...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html -
OneVsOneClassifier — scikit-learn 1.7.0 documen...
X_test [: 10 ]) array([2, 1, 0, 2, 0, 2, 0, 1, 1, 1]) decision_function...n_classes * (n_classes - 1) / 2 classifiers, this method is usually...scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsOneClassifier.html -
GammaRegressor — scikit-learn 1.7.0 documentation
determination R^2. R^2 uses squared error and D^2 uses the deviance...GammaRegressor () >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html -
index.css
--sk-landing-bg-2: var(--sk-cyan-shades-2); --sk-landing-bg-3:...var(--sk-cyan-shades-3); --sk-landing-bg-2: var(--sk-cyan); --sk-landing-bg-3:...scikit-learn.org/stable/_static/styles/index.css -
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 -
cluster_optics_dbscan — scikit-learn 1.7.0 docu...
2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8... ( ... X , ... min_samples = 2 , ... max_eps = np . inf , ......scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.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 -
StratifiedKFold — scikit-learn 1.7.0 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...n_splits = 2 ) >>> skf . get_n_splits ( X , y ) 2 >>> print (...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html