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  1. compute_sample_weight — scikit-learn 1.7.2 docu...

    [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}] . The "balanced" mode uses...
    scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_sample_weight.html
    Sat Nov 01 09:15:33 UTC 2025
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  2. SkewedChi2Sampler — scikit-learn 1.7.2 document...

    [ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SkewedChi2Sampler ( * , skewedness = 1.0 , n_components = 100 , random_state...
    scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.SkewedChi2Sampler.html
    Mon Nov 03 14:20:03 UTC 2025
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  3. trustworthiness — scikit-learn 1.7.2 documentation

    1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...
    scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html
    Mon Nov 03 14:20:03 UTC 2025
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  4. safe_mask — scikit-learn 1.7.2 documentation

    csr_matrix >>> data = csr_matrix ([[ 1 ], [ 2 ], [ 3 ], [ 4 ], [ 5 ]])...
    scikit-learn.org/stable/modules/generated/sklearn.utils.safe_mask.html
    Sat Nov 01 09:15:33 UTC 2025
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  5. Simple 1D Kernel Density Estimation — scikit-le...

    1 , int ( 0.3 * N )), np . random . normal ( 5 , 1 , int...score_samples ( X_plot ) ax [ 1 , 1 ] . fill ( X_plot [:, 0 ], np...
    scikit-learn.org/stable/auto_examples/neighbors/plot_kde_1d.html
    Mon Nov 03 14:20:04 UTC 2025
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  6. compute_optics_graph — scikit-learn 1.7.2 docum...

    1. , 1. , 4.12]) >>> reachability array([ inf, 3.16, 1.41,...1.41, 4.12, 1. , 5. ]) >>> predecessor array([-1, 0, 1, 5, 3, 2])...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html
    Mon Nov 03 14:20:03 UTC 2025
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  7. 3. Model selection and evaluation — scikit-lear...

    1.1. Computing cross-validated metrics 3.1.2. Cross...validation iterators 3.1.3. A note on shuffling 3.1.4. Cross validation...
    scikit-learn.org/stable/model_selection.html
    Mon Nov 03 14:20:05 UTC 2025
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  8. VarianceThreshold — scikit-learn 1.7.2 document...

    1 , 4 , 3 ], [ 0 , 1 , 1 , 3 ]] >>> selector...fit_transform ( X ) array([[2, 0], [1, 4], [1, 1]]) fit ( X , y = None )...
    scikit-learn.org/stable/modules/generated/sklearn.feature_selection.VarianceThreshold.html
    Mon Nov 03 14:20:05 UTC 2025
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  9. Successive Halving Iterations — scikit-learn 1....

    "max_features" : randint ( 1 , 6 ), "min_samples_split" : randint...min_samples_split 5 min_samples_leaf 1 min_weight_fraction_leaf 0.0 max_features...
    scikit-learn.org/stable/auto_examples/model_selection/plot_successive_halving_iterations.html
    Mon Nov 03 14:20:05 UTC 2025
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  10. d2_tweedie_score — scikit-learn 1.7.2 documenta...

    1 , 2.5 , 7 ] >>> y_pred = [ 1 , 1 , 5 , 3.5 ] >>>...explained. Best possible score is 1.0 and it can be negative (because...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_tweedie_score.html
    Mon Nov 03 14:20:04 UTC 2025
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