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  1. feature_extraction.rst.txt

    array([[1, 1, 1, 0, 1, 1, 1, 0], [1, 1, 0, 1, 1, 1, 0, 1]]) In...array([[0, 1, 1, 1, 0, 0, 1, 0, 1], [0, 1, 0, 1, 0, 2, 1, 0, 1], [1,...
    scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt
    Thu Dec 04 11:53:53 GMT 2025
      43.4K bytes
     
  2. plot_classifier_comparison.rst.txt

    C=1, random_state=42), GaussianProcessClass(1.0 * RBF(1.0),...max_features=1, random_state=42 ), MLPClassifier(alpha=1, max_iter=1000,...
    scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt
    Fri Dec 05 17:52:54 GMT 2025
      7.8K bytes
     
  3. preprocessing.rst.txt

    1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1], ...,...0. , -1.22, 1.33 ], [ 1.22, 0. , -0.267], [-1.22, 1.22, -1.06 ]])...
    scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt
    Thu Dec 04 11:53:54 GMT 2025
      52.9K bytes
     
  4. getting_started.rst.txt

    dataset is easy array([1., 1., 1., 1., 1.]) Automatic parameter...ransform(X) array([[-1., 1.], [ 1., -1.]]) Sometimes, you want...
    scikit-learn.org/stable/_sources/getting_started.rst.txt
    Thu Dec 04 11:53:55 GMT 2025
      10.3K bytes
     
  5. clustering.rst.txt

    1, 1, 1] >>> labels_pred = [0, 0, 1, 1, 2, 2] >>>...= [0, 0, 0, 1, 1, 1] >>> labels_pred = [0, 0, 1, 1, 2, 2] >>>...
    scikit-learn.org/stable/_sources/modules/clustering.rst.txt
    Fri Dec 05 17:52:54 GMT 2025
      92.8K bytes
     
  6. model_evaluation.rst.txt

    1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...0, 0, 1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...
    scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt
    Sat Nov 29 05:08:38 GMT 2025
      132.2K bytes
     
  7. cross_validation.rst.txt

    [1., 1.], [-1., -1.], [2., 2.]]) >>> y = np.array([0, 1, 0,...3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3] [0 1]...
    scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt
    Tue Dec 02 16:12:16 GMT 2025
      41.1K bytes
      1 views
     
  8. ensemble.rst.txt

    1, 2, np.nan]).reshape(-1, 1) >>> y = [0, 0, 1, 1] >>> gbdt...np.nan, 1, 2, np.nan]).reshape(-1, 1) >>> y = [0, 1, 0, 0, 1] >>>...
    scikit-learn.org/stable/_sources/modules/ensemble.rst.txt
    Fri Dec 05 17:52:54 GMT 2025
      72.2K bytes
     
  9. plot_release_highlights_1_7_0.rst.txt

    #sk-container-id-1 pre { padding: 0; } #sk-container-id-1 input.sk-hidden--visually...ound); flex-grow: 1; } #sk-container-id-1 div.sk-parallel { display:...
    scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_7_0.r...
    Fri Dec 05 17:52:54 GMT 2025
      66.3K bytes
     
  10. neighbors.rst.txt

    array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])...np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])...
    scikit-learn.org/stable/_sources/modules/neighbors.rst.txt
    Fri Dec 05 17:52:55 GMT 2025
      37.9K bytes
     
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