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Overview of multiclass training meta-estimators...
set_xlabel ( "Accuracy score" ) ax . set_xlim ([ 0 , 0.7 ]) _ = ax ....predictive model. y . value_counts () . sort_index () class_protein_localization...scikit-learn.org/stable/auto_examples/multiclass/plot_multiclass_overview.html -
Compare the effect of different scalers on data...
PowerTransformer ( method = "box-cox" ) . fit_transform ( X ), ), ( "Data...scaling" , MaxAbsScaler () . fit_transform ( X )), ( "Data after robust...scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html -
Label Propagation digits: Active learning — sci...
0 0 0 0 23 0 0 0 10] [ 0 1 0 0 0 0 34 0 0 0] [ 0 0 0 0 0 0 0...1.00 22 1 0.79 1.00 0.88 22 2 1.00 0.93 0.96 29 3 1.00 1.00 1.00...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
SVM: Maximum margin separating hyperplane — sci...
= 0.5 , linestyles = [ "--" , "-" , "--" ], ax = ax , ) # plot...plot_method = "contour" , colors = "k" , levels = [ - 1 , 0 , 1 ], alpha...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html -
ridge_regression — scikit-learn 1.7.2 documenta...
version 0.17. solver {‘auto’, ‘svd’, ‘cholesky’, ‘lsqr’, ‘sparse_cg’,...‘sparse_cg’, ‘sag’, ‘saga’, ‘lbfgs’}, default=’auto’ Solver to use...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ridge_regression.html -
VarianceThreshold — scikit-learn 1.7.2 document...
= [[ 0 , 2 , 0 , 3 ], [ 0 , 1 , 4 , 3 ], [ 0 , 1 , 1 , 3 ]] >>>...generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.VarianceThreshold.html -
sklearn.frozen — scikit-learn 1.7.2 documentation
top Ctrl + K GitHub Choose version sklearn.frozen # FrozenEstimator...fitted estimator to prevent re-fitting....scikit-learn.org/stable/api/sklearn.frozen.html -
SelectFdr — scikit-learn 1.7.2 documentation
generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features..., alpha = 0.01 ) . fit_transform ( X , y ) >>> X_new . shape...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFdr.html -
orthogonal_mp — scikit-learn 1.7.2 documentation
12. (December 1993), pp. 3397-3415. ( https://www.di.ens.fr/~m...orthogonal_mp ( X , y ) >>> coef . shape (100,) >>> X [: 1 ,] @ coef...scikit-learn.org/stable/modules/generated/sklearn.linear_model.orthogonal_mp.html -
maxabs_scale — scikit-learn 1.7.2 documentation
independently array([[-1. , 0.5, 1. ], [-1. , 0. , 1. ]]) On this page...1. ], [-0.5, 0. , 0.5]]) >>> maxabs_scale ( X , axis = 1 ) #...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html