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  1. single_source_shortest_path_length — scikit-lea...

    1), (1, 1), (2, 0), (3, 1), (4, 1), (5, 1)] On this...([[ 0 , 1 , 0 , 0 ], ... [ 1 , 0 , 1 , 0 ], ... [ 0 , 1 , 0 , 0...
    scikit-learn.org/stable/modules/generated/sklearn.utils.graph.single_source_shortest_path_length....
    Sat Aug 02 00:15:38 UTC 2025
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  2. Concatenating multiple feature extraction metho...

    features__univ_select__k=1, svm__C=0.1 [CV 1/5; 1/18] END features_...nts=1, features__univ_select__k=1, svm__C=0.1;, score=1.000 total...
    scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html
    Sat Aug 02 00:15:37 UTC 2025
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  3. Permutation Importance vs Random Forest Feature...

    unknown_value =- 1 , encoded_missing_value =- 1 ) numerical_pipe...'use_encoded_value' unknown_value -1 encoded_missing_value -1 min_frequency None...
    scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance.html
    Sat Aug 02 00:15:37 UTC 2025
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  4. Version 0.17 — scikit-learn 1.7.1 documentation

    1 # February 18, 2016 Changelog...meta-estimator with n_jobs > 1 used with a large grid of parameters...
    scikit-learn.org/stable/whats_new/v0.17.html
    Sat Aug 02 00:15:36 UTC 2025
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  5. Normal, Ledoit-Wolf and OAS Linear Discriminant...

    n_features_range = range ( 1 , n_features_max + 1 , step ) for n_features...n_samples = n_samples , n_features = 1 , centers = [[ - 2 ], [ 2 ]])...
    scikit-learn.org/stable/auto_examples/classification/plot_lda.html
    Sat Aug 02 00:15:37 UTC 2025
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  6. precision_recall_curve — scikit-learn 1.7.1 doc...

    y_true is in {-1, 1} or {0, 1}, pos_label is set to 1, otherwise...0.66666667, 0.5 , 1. , 1. ]) >>> recall array([1. , 1. , 0.5, 0.5,...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html
    Sat Aug 02 00:15:35 UTC 2025
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  7. Post-hoc tuning the cut-off point of decision f...

    0001 C 1.0 fit_intercept True intercept_scaling 1 class_weight...tuned_model_coef . boxplot ( ax = ax [ 1 ]) ax [ 1 ] . set_title ( "Tuned model"...
    scikit-learn.org/stable/auto_examples/model_selection/plot_tuned_decision_threshold.html
    Sat Aug 02 00:15:37 UTC 2025
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  8. Demonstration of k-means assumptions — scikit-l...

    axs [ 1 , 0 ] . set_title ( "Unequal Variance" ) axs [ 1 , 1 ] ....X_filtered [:, 1 ], c = y_filtered ) axs [ 1 , 1 ] . set_title...
    scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html
    Sat Aug 02 00:15:35 UTC 2025
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  9. non_negative_factorization — scikit-learn 1.7.1...

    array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...n\_samples * ||vec(H)||_1\\ &+ 0.5 * alpha\_W * (1 - l1\_ratio) * n\_features...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.non_negative_factorization.html
    Sat Aug 02 00:15:38 UTC 2025
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  10. Recognizing hand-written digits — scikit-learn ...

    0 0 0 1 0 0 0 0 0] [ 0 88 1 0 0 0 0 0 1 1] [ 0 0 85 1 0 0 0 0...0 0 88 1 0 0 2] [ 0 1 0 0 0 0 90 0 0 0] [ 0 0 0 0 0 1 0 88 0...
    scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html
    Sat Aug 02 00:15:37 UTC 2025
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