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Comparing Target Encoder with Other Encoders — ...
pipe ): result = cross_validate ( pipe , X , y , scoring...categorical_features ), ] ) pipe = make_pipeline ( preprocessor...scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder.html -
Displaying Pipelines — scikit-learn 1.5.0 docum...
] pipe = Pipeline ( steps ) pipe # click on the...= "linear" ))] pipe = Pipeline ( steps ) pipe # click on the...scikit-learn.org/stable/auto_examples/miscellaneous/plot_pipeline_display.html -
Selecting dimensionality reduction with Pipelin...
load_digits ( return_X_y = True ) pipe = Pipeline ( [ ( "scaling" ,...f)" ] grid = GridSearchCV ( pipe , n_jobs = 1 , param_grid =...scikit-learn.org/stable/auto_examples/compose/plot_compare_reduction.html -
Categorical Feature Support in Gradient Boostin...
for pipe in ( hist_dropped , hist_one_hot...hist_ordinal , hist_native ): if pipe is hist_native : # The native...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html -
Balance model complexity and cross-validated sc...
argmin () ] return best_idx pipe = Pipeline ( [ ( "reduce_dim"...14 ]} grid = GridSearchCV ( pipe , cv = 10 , n_jobs = 1 , param_grid...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_refit_callable.html -
Introducing the set_output API — scikit-learn 1...
transform_output = "pandas" ) num_pipe = make_pipeline ( SimpleImputer...ColumnTransformer ( ( ( "numerical" , num_pipe , num_cols ), ( "categorical"...scikit-learn.org/stable/auto_examples/miscellaneous/plot_set_output.html -
maxabs_scale — scikit-learn 1.5.0 documentation
most risks of data leaking: pipe = make_pipeline(MaxAbsScaler(),...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html -
Permutation Importance vs Random Forest Feature...
encoded_missing_value =- 1 ) numerical_pipe = SimpleImputer ( strategy =...categorical_columns ), ( "num" , numerical_pipe , numerical_columns ), ], v...scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance.html -
1.6. Nearest Neighbors — scikit-learn 1.5.0 doc...
( n_neighbors = 3 ) >>> nca_pipe = Pipeline ([( 'nca' , nca ),...), ( 'knn' , knn )]) >>> nca_pipe . fit ( X_train , y_train )...scikit-learn.org/stable/modules/neighbors.html -
Metadata Routing — scikit-learn 1.5.0 documenta...
pipe = SimplePipeline ( transformer...( sample_weight = True ), ) pipe . fit ( X , y , sample_weight...scikit-learn.org/stable/auto_examples/miscellaneous/plot_metadata_routing.html