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  1. Column Transformer with Heterogeneous Data Sour...

    random_state = 1 , subset = "train" , categories = categories ,...y_test = fetch_20newsgroups ( random_state = 1 , subset = "test"...
    scikit-learn.org/stable/auto_examples/compose/plot_column_transformer.html
    Thu Apr 10 21:02:03 UTC 2025
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  2. FastICA — scikit-learn 1.6.1 documentation

    fun = 'logcosh' , fun_args = None , max_iter = 200 , tol = 0.0001...n_components = None , * , algorithm = 'parallel' , whiten = 'unit-variance'...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.FastICA.html
    Thu Apr 10 21:02:03 UTC 2025
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  3. Density Estimation for a Gaussian mixture — sci...

    CS = plt . contour ( X , Y , Z , norm = LogNorm ( vmin = 1.0...CB = plt . colorbar ( CS , shrink = 0.8 , extend = "both" ) plt...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_pdf.html
    Thu Apr 10 21:02:03 UTC 2025
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  4. NuSVC — scikit-learn 1.6.1 documentation

    nu = 0.5 , kernel = 'rbf' , degree = 3 , gamma = 'scale'...coef0 = 0.0 , shrinking = True , probability = False , tol = 0.001...
    scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html
    Thu Apr 10 21:02:04 UTC 2025
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  5. k_means — scikit-learn 1.6.1 documentation

    sample_weight = None , init = 'k-means++' , n_init = 'auto' , max_iter...max_iter = 300 , verbose = False , tol = 0.0001 , random_state...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html
    Thu Apr 10 21:02:04 UTC 2025
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  6. Kernel Density Estimation — scikit-learn 1.6.1 ...

    pca = PCA ( n_components = 15 , whiten = False ) data = pca ....new_data = kde . sample ( 44 , random_state = 0 ) new_data = pca ....
    scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html
    Thu Apr 10 21:02:04 UTC 2025
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  7. LeavePOut — scikit-learn 1.6.1 documentation

    Train: index=[2 3] Test: index=[0 1] Fold 1: Train: index=[1 3] Test:...Test: index=[0 2] Fold 2: Train: index=[1 2] Test: index=[0 3] Fold...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePOut.html
    Thu Apr 10 21:02:03 UTC 2025
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  8. Univariate Feature Selection — scikit-learn 1.6...

    y = load_iris ( return_X_y = True ) # Some noisy...y_train , y_test = train_test_split ( X , y , stratify = y , random_state...
    scikit-learn.org/stable/auto_examples/feature_selection/plot_feature_selection.html
    Thu Apr 10 21:02:03 UTC 2025
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  9. Recursive feature elimination with cross-valida...

    n_informative = 3 , n_redundant = 2 , n_repeated = 0 , n_classes = 8 ,..., y = make_classification ( n_samples = 500 , n_features = 15...
    scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_with_cross_validation.html
    Thu Apr 10 21:02:03 UTC 2025
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  10. Blind source separation using FastICA — scikit-...

    n_samples = 2000 time = np . linspace ( 0 , 8 , n_samples ) s1 = np...( size = S . shape ) # Add noise S /= S . std ( axis = 0 ) # Standardize...
    scikit-learn.org/stable/auto_examples/decomposition/plot_ica_blind_source_separation.html
    Thu Apr 10 21:02:03 UTC 2025
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