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  1. fbeta_score — scikit-learn 1.7.2 document...

    2 , 0 , 1 , 2 ] >>> y_pred = [ 0 , 2 , 1 , 0...\frac{(1 + \beta^2) \text{tp}} {(1 + \beta^2) \text{tp} + \text{fp}...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html
    Fri Dec 05 17:52:54 GMT 2025
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  2. incr_mean_variance_axis — scikit-learn 1....

    2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.incr_mean_variance_axis.html
    Fri Nov 21 09:29:39 GMT 2025
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  3. KernelCenterer — scikit-learn 1.7.2 docum...

    - 2. , 2. ], ... [ - 2. , 1. , 3. ], ... [ 4. , 1. , - 2. ]]...K array([[ 9., 2., -2.], [ 2., 14., -13.], [ -2., -13., 21.]])...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KernelCenterer.html
    Thu Dec 04 11:53:54 GMT 2025
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  4. inplace_swap_row — scikit-learn 1.7.2 doc...

    2 , 2 ]) >>> data = np . array ([ 8 , 2 , 5 ])...>>> indptr = np . array ([ 0 , 2 , 3 , 3 , 3 ]) >>> indices...
    scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_swap_row.html
    Fri Nov 21 09:29:40 GMT 2025
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  5. grid_to_graph — scikit-learn 1.7.2 docume...

    'int64' with 2 stored elements and shape (2, 2)> Coords Values...>>> mask [[ 1 , 2 ], [ 1 , 2 ], :] = True >>>...
    scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.grid_to_graph.html
    Fri Dec 05 17:52:54 GMT 2025
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  6. weighted_mode — scikit-learn 1.7.2 docume...

    2 , 4 , 2 ] >>> weights = [...weights ) (array([2.]), array([3.5])) The value 2 has the highest...
    scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.weighted_mode.html
    Fri Nov 21 09:29:38 GMT 2025
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  7. LinearSVR — scikit-learn 1.7.2 documentation

    float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...(n_features) if n_classes == 2 else (n_classes, n_features) Weights...
    scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVR.html
    Fri Dec 05 17:52:55 GMT 2025
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  8. k_means — scikit-learn 1.7.2 documentation

    2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...>>> centroid array([[10., 2.], [ 1., 2.]]) >>> label array([1,...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html
    Fri Dec 05 17:52:55 GMT 2025
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  9. check_X_y — scikit-learn 1.7.2 documentation

    2 ], [ 3 , 4 ], [ 5 , 6 ]] >>> y = [ 1 , 2 , 3 ]...array([[1, 2], [3, 4], [5, 6]]) >>> y array([1, 2, 3]) On...
    scikit-learn.org/stable/modules/generated/sklearn.utils.check_X_y.html
    Thu Dec 04 11:53:54 GMT 2025
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  10. make_friedman3 — scikit-learn 1.7.2 docum...

    in Friedman [1] and Breiman [2]. Inputs X are 4 independent features...<= 560 * pi , 0 <= X [:, 2 ] <= 1 , 1 <= X [:, 3 ]...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman3.html
    Fri Dec 05 17:52:55 GMT 2025
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