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Results 31 - 40 of 132 for pipe (0.08 sec)

  1. 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
    Sat May 18 15:26:00 UTC 2024
      56.4K bytes
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  2. Getting Started — scikit-learn 1.4.2 documentation

    create a pipeline object >>> pipe = make_pipeline ( ... StandardScaler...# fit the whole pipeline >>> pipe . fit ( X_train , y_train )...
    scikit-learn.org/stable/getting_started.html
    Sat May 18 15:26:00 UTC 2024
      40K bytes
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  3. 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
    Sat May 18 15:26:01 UTC 2024
      77K bytes
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  4. 1. Metadata Routing — scikit-learn 1.4.2 docume...

    = SelectKBest ( k = 2 ) >>> pipe = make_pipeline ( sel , lr )...cv_results = cross_validate ( ... pipe , ... X , ... y , ... cv = GroupKFold...
    scikit-learn.org/stable/metadata_routing.html
    Sat May 18 15:26:00 UTC 2024
      64.2K bytes
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  5. sklearn.preprocessing.maxabs_scale — scikit-lea...

    most risks of data leaking: pipe = make_pipeline(MaxAbsScaler(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html
    Sat May 18 15:26:00 UTC 2024
      19.5K bytes
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  6. sklearn.preprocessing.scale — scikit-learn 1.4....

    most risks of data leaking: pipe = make_pipeline(StandardScaler(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html
    Sat May 18 15:26:01 UTC 2024
      21.2K bytes
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  7. Elasticsearch: The Official Distributed Search ...

    and from a piped query language. Start simple...
    www.elastic.co/elasticsearch
    Sun May 19 00:03:22 UTC 2024
      563.4K bytes
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  8. sklearn.preprocessing.power_transform — scikit-...

    : pipe = make_pipeline(PowerTransformer(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.power_transform.html
    Sat May 18 15:26:01 UTC 2024
      22.4K bytes
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  9. 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
    Sat May 18 15:26:00 UTC 2024
      95K bytes
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  10. Elastic Security Solution | Elastic

    nimble piped queries, and end-to-end case...
    www.elastic.co/security
    Sun May 19 00:05:10 UTC 2024
      533.7K bytes
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