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robust_scale — scikit-learn 1.7.2 documentation
robust_scale >>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>> robust_scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.robust_scale.html -
orthogonal_mp — scikit-learn 1.7.2 documentation
n_nonzero_coefs : argmin ||y - Xgamma||^2 subject to ||gamma||_0 <= n_{nonzero...||gamma||_0 subject to ||y - Xgamma||^2 <= tol Read more in the User Guide...scikit-learn.org/stable/modules/generated/sklearn.linear_model.orthogonal_mp.html -
API Reference — scikit-learn 1.7.2 documentation
make_friedman2 Generate the “Friedman #2” regression problem. sklearn.datasets...sklearn.datasets make_hastie_10_2 Generate data for binary classification...scikit-learn.org/stable/api/index.html -
7. Dataset transformations — scikit-learn 1.7.2...
2.2. Feature hashing 7.2.3. Text feature extraction...Composite Estimators 7.2. Feature extraction 7.2.1. Loading features...scikit-learn.org/stable/data_transforms.html -
Comparison of LDA and PCA 2D projection of Iris...
the different samples on the 2 first principal components. Linear...target_names pca = PCA ( n_components = 2 ) X_r = pca . fit ( X ) . transform...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_vs_lda.html -
Compare cross decomposition methods — scikit-le...
[: n // 2 ] Y_train = Y [: n // 2 ] X_test = X [ n // 2 :] Y_test...that: Y = XB + Err) [[1 1 1] [2 2 2] [0 0 0] [0 0 0] [0 0 0] [0...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_compare_cross_decomposition.html -
homogeneity_completeness_v_measure — scikit-lea...
2 , 2 ], [ 0 , 0 , 1 , 2 , 2 , 2 ] >>> homogen...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_completeness_v_measure.html -
mean_squared_log_error — scikit-learn 1.7.2 doc...
2 ], [ 7 , 6 ]] >>> y_pred = [[ 0.5 , 2 ], [ 1 , 2.5 ],...y_true = [ 3 , 5 , 2.5 , 7 ] >>> y_pred = [ 2.5 , 5 , 4 , 8 ] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_log_error.html -
7.9. Transforming the prediction target (y) — s...
array([2, 2, 1]) >>> list ( le . inverse_transform ([ 2 , 2 , 1...y = [[ 2 , 3 , 4 ], [ 2 ], [ 0 , 1 , 3 ], [ 0 , 1 , 2 , 3 , 4...scikit-learn.org/stable/modules/preprocessing_targets.html -
SGD: Maximum margin separating hyperplane — sci...
centers = 2 , random_state = 0 , cluster_std...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html