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Probability Calibration curves — scikit-learn 1...
add_subplot ( gs [: 2 , : 2 ]) calibration_displays = {}...histogram grid_positions = [( 2 , 0 ), ( 2 , 1 ), ( 3 , 0 ), ( 3 ,...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
PLSSVD — scikit-learn 1.8.0 documentation
[ 2. , 2. , 2. ], ... [ 2. , 5. , 4. ]]) >>>...([[ 0.1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9 ], ... [...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
RegressorChain — scikit-learn 1.8.0 documentation
2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain = RegressorChain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html -
feature_extraction.rst.txt
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...(one_image, (2, 2)) >>> patches.shape (9, 2, 2, 3) >>> patches[4,...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
mean_gamma_deviance — scikit-learn 1.8.0 docume...
= [ 2 , 0.5 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2. ] >>>...with the power parameter power=2 . It is invariant to scaling of...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_gamma_deviance.html -
Concatenating multiple feature extraction metho...
0s [CV 2/5; 2/18] START features__pca__n_components=1,...features__univ_select__k=1, svm__C=1 [CV 2/5; 2/18] END features__pca__n_components=1,...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
randomized_svd — scikit-learn 1.8.0 documentation
2), (2,), (2, 4)) On this page This Page...increase this parameter up to 2*k - n_components where k is the...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html -
Linear and Quadratic Discriminant Analysis with...
[ 2.5 , 0.7 ]]) * 2.0 cov_class_2 = cov_class_1.... Ellipse ( mean , 2 * v [ 0 ] ** 0.5 , 2 * v [ 1 ] ** 0.5 ,...scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html -
7.4. Imputation of missing values — scikit-lear...
2. Univariate feature imputation...'mean' ) >>> imp . fit ([[ 1 , 2 ], [ np . nan , 3 ], [ 7 , 6 ]])...scikit-learn.org/stable/modules/impute.html -
L1-based models for Sparse Signals — scikit-lea...
linspace ( - 2 , 2 , n_samples ) freqs = 2 * np . pi * np ....time_step + 2 * ( rng . random_sample () - 0.5 )) X [:, i ] += 0.2 * rng...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html