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make_gaussian_quantiles — scikit-learn 1....
int64(2), np.int64(0), np.int64(1), np.int64(0), np.int64(2)] Gallery...n_samples = 100 , n_features = 2 , n_classes = 3 , shuffle = True...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html -
d2_pinball_score — scikit-learn 1.8.0 doc...
Notes Like \(R^2\) , \(D^2\) score may be negative (it...], [ 2 ], [ 3 ], [ 4 ]]) >>> y = np . array ([ 2.5 ,...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_pinball_score.html -
VotingClassifier — scikit-learn 1.8.0 doc...
[ - 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.ensemble.VotingClassifier.html -
mean_gamma_deviance — scikit-learn 1.8.0 ...
2. , 2. ] >>> mean_gamma_deviance...with the power parameter power=2 . It is invariant to scaling of...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_gamma_deviance.html -
Plot randomly generated multilabel dataset R...
1500 * p_c ** 2 , color = COLORS . take ([ 1 , 2 , 4 ]), ) ax...means the class is present: 1 2 3 Color Y N N Red N Y N Blue N...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
sort_graph_by_row_values — scikit-learn 1...
2. ], ... [ 1. , 2. , 0. ]]) >>>.... data array([3., 1., 3., 2., 1., 2.]) >>> X_ = sort...scikit-learn.org/stable/modules/generated/sklearn.neighbors.sort_graph_by_row_values.html -
sphinx-design.min.css
sd-g-2,.sd-gy-2{--sd-gutter-y: 0.5rem}.sd-g-2,.sd-gx-2{--sd-gutter-x:...!important}.sd-p-2{padding:.5rem !important}.sd-pt-2,.sd-py-2{padding-top:.5rem...scikit-learn.org/stable/_static/sphinx-design.min.css -
Ledoit-Wolf vs OAS estimation — scikit-le...
subplot ( 2 , 1 , 2 ) plt . errorbar ( n_samples_range...shrinkage_ # plot MSE plt . subplot ( 2 , 1 , 1 ) plt . errorbar ( n_samples_range...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
LassoLarsIC — scikit-learn 1.8.0 document...
[[ - 2 , 2 ], [ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...>>> y = [ - 2.2222 , - 1.1111 , 0 , - 1.1111 , - 2.2222 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
1.5. Stochastic Gradient Descent — scikit...
:= \frac{1}{2} \sum_{j=1}^{m} w_j^2 = ||w||_2^2\) , \(L_1\) norm:...>>> clf . predict ([[ 2. , 2. ]]) array([1]) SGD fits a...scikit-learn.org/stable/modules/sgd.html