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Probability Calibration for 3-class classificat...
"($\frac {1}{2} $, $0$, $\frac {1}{2} $)" , xy = (..."($0$, $\frac {1}{2} $, $\frac {1}{2} $)" , xy = ( 0.0...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_multiclass.html -
Model Complexity Influence — scikit-learn...
"n_iter_no_change" : 2 , }, "changing_param"..."C" : 1e3 , "gamma" : 2 **- 15 }, "changing_param"...scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html -
Principal Component Regression vs Partial Least...
n_samples ) / 2 fig , axes = plt . subplots ( 1 , 2 , figsize =...) pca = PCA ( n_components = 2 ) . fit ( X ) plt . scatter (...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_pcr_vs_pls.html -
mean_absolute_percentage_error — scikit-l...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>..., 0. , 2.4 , 7. ] >>> y_pred = [ 1.2 , 0.1 , 2.4 , 8....scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_percentage_error.html -
LeaveOneGroupOut — scikit-learn 1.8.0 doc...
Fold 0: Train: index=[2 3], group=[2 2] Test: index=[0 1], group=[1...group=[1 1] Test: index=[2 3], group=[2 2] get_metadata_routing...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeaveOneGroupOut.html -
Two-class AdaBoost — scikit-learn 1.8.0 d...
cov = 2.0 , n_samples = 200 , n_features = 2 , n_classes = 2 , random_state...= 300 , n_features = 2 , n_classes = 2 , random_state = 1 ) X...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html -
mean_poisson_deviance — scikit-learn 1.8....
= [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2....2. ] >>> mean_poisson_deviance ( y_true , y_pred ) 1.4260......scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html -
preprocessing.rst.txt
2. , 1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1],...4.1, 6.7, 2.5], [7.7, 4.2, 6.7, 2.5], [7.9, 4.4, 6.9, 2.5]]) Thus...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
QuadraticDiscriminantAnalysis — scikit-le...
[ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
IsotonicRegression — scikit-learn 1.8.0 d...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...Operations Research Vol. 14, No. 2 (May, 1989), pp. 303-308 Isotone...scikit-learn.org/stable/modules/generated/sklearn.isotonic.IsotonicRegression.html