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Results 11 - 20 of 59 for pipe (0.09 sec)

  1. 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
    Fri May 31 14:06:04 UTC 2024
      135.4K bytes
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  2. One-Class SVM versus One-Class SVM using Stocha...

    1e-4 ) pipe_sgd = make_pipeline ( transform , clf_sgd ) pipe_sgd...y_pred_train_sgd = pipe_sgd . predict ( X_train ) y_pred_test_sgd = pipe_sgd...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgdocsvm_vs_ocsvm.html
    Fri May 31 14:06:04 UTC 2024
      121.1K bytes
      1 views
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  3. 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
    Fri May 31 14:06:06 UTC 2024
      204.6K bytes
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  4. 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
    Fri May 31 14:06:04 UTC 2024
      98.9K bytes
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  5. 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
    Fri May 31 14:06:06 UTC 2024
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  6. 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
    Fri May 31 14:06:04 UTC 2024
      123.8K bytes
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  7. 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
    Fri May 31 14:06:06 UTC 2024
      138.5K bytes
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  8. 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
    Fri May 31 14:06:04 UTC 2024
      115.9K bytes
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  9. robust_scale — scikit-learn 1.5.0 documentation

    most risks of data leaking: pipe = make_pipeline(RobustScaler(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.robust_scale.html
    Thu May 30 15:22:07 UTC 2024
      119.1K bytes
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  10. scale — scikit-learn 1.5.0 documentation

    most risks of data leaking: pipe = make_pipeline(StandardScaler(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html
    Sat May 25 13:41:01 UTC 2024
      117.6K bytes
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