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  1. AffinityPropagation — scikit-learn 1.5.2 docume...

    damping = 0.5 , max_iter = 200 , convergence_iter = 15 , copy...copy = True , preference = None , affinity = 'euclidean' , verbose...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.AffinityPropagation.html
    Thu Nov 21 22:17:08 UTC 2024
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  2. SVM: Weighted samples — scikit-learn 1.5.2 docu...

    c = y , s = 100 * sample_weight , alpha = 0.9 , cmap = plt...( xx , yy , Z , alpha = 0.75 , cmap = plt . cm . bone ) axis...
    scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html
    Wed Nov 20 19:47:14 UTC 2024
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  3. AdditiveChi2Sampler — scikit-learn 1.5.2 docume...

    y = load_digits ( return_X_y = True ) >>> chi2sampler = AdditiveChi2Sampler...>>> clf = SGDClassifier ( max_iter = 5 , random_state = 0 , tol...
    scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.AdditiveChi2Sampler.html
    Thu Nov 21 22:17:10 UTC 2024
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  4. Birch — scikit-learn 1.5.2 documentation

    threshold = 0.5 , branching_factor = 50 , n_clusters = 3 , compute_labels...compute_labels = True , copy = True ) [source] # Implements the...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.Birch.html
    Thu Nov 21 22:17:08 UTC 2024
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  5. glossary.rst.txt

    _glossary: ========== Glossary of Common Terms and API Elements ==========...props`. General Concepts ========== .. glossary:: 1d 1d array...
    scikit-learn.org/stable/_sources/glossary.rst.txt
    Wed Nov 20 19:47:14 UTC 2024
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  6. Factor Analysis (with rotation) to visualize pa...

    cmap = "RdBu_r" , vmin =- 1 , vmax = 1 ) ax . set_xticks...ncols = len ( methods ), figsize = ( 10 , 8 ), sharey = True )...
    scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html
    Thu Nov 21 22:17:08 UTC 2024
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  7. fetch_openml — scikit-learn 1.5.2 documentation

    n_retries : int = 3 , delay : float = 1.0 , parser : str = 'auto' ,...: str | None = None , * , version : str | int = 'active' , data_id...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html
    Thu Nov 21 22:17:10 UTC 2024
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  8. Isotonic Regression — scikit-learn 1.5.2 docume...

    check_random_state n = 100 x = np . arange ( n ) rs = check_random_state...models: ir = IsotonicRegression ( out_of_bounds = "clip" ) y_ = ir ....
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_isotonic_regression.html
    Thu Nov 21 22:17:09 UTC 2024
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  9. 1.12. Multiclass and multioutput algorithms — s...

    n_informative = 30 , n_classes = 3 , ... random_state = 1 ) >>> y2 = shuffle..., y = datasets . load_iris ( return_X_y = True ) >>> clf = OutputCodeClassifier...
    scikit-learn.org/stable/modules/multiclass.html
    Thu Nov 21 22:17:10 UTC 2024
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  10. An example of K-Means++ initialization — scikit...

    data n_samples = 4000 n_components = 4 X , y_true = make_blobs (...n_samples = n_samples , centers = n_components , cluster_std = 0.60...
    scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_plusplus.html
    Thu Nov 21 22:17:09 UTC 2024
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