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  1. enet_path — scikit-learn 1.7.1 documentation

    l1_ratio = 0.5 , eps = 0.001 , n_alphas = 100 , alphas = None ,...precompute = 'auto' , Xy = None , copy_X = True , coef_init = None...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.enet_path.html
    2025-07-18 16:24
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  2. LocallyLinearEmbedding — scikit-learn 1.7.1 doc...

    n_neighbors = 5 , n_components = 2 , reg = 0.001 , eigen_solver = 'auto'...'auto' , tol = 1e-06 , max_iter = 100 , method = 'standard' , hessian_tol...
    scikit-learn.org/stable/modules/generated/sklearn.manifold.LocallyLinearEmbedding.html
    2025-07-18 16:24
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  3. Release Highlights for scikit-learn 1.3 — sciki...

    random_state = rng ) coef = rng . uniform ( low =- 10 , high = 20 , size...size = n_features ) y = rng . gamma ( shape = 2 , scale = np ....
    scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html
    2025-07-18 16:23
      116.6K bytes
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  4. MiniBatchNMF — scikit-learn 1.7.1 documentation

    max_iter = 200 , alpha_W = 0.0 , alpha_H = 'same' , l1_ratio = 0.0...n_components = 'auto' , * , init = None , batch_size = 1024 , beta_loss...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchNMF.html
    2025-07-18 16:24
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  5. check_array — scikit-learn 1.7.1 documentation

    accept_sparse = False , * , accept_large_sparse = True , dtype = 'numeric'...'numeric' , order = None , copy = False , force_writeable = False , force_all_finite...
    scikit-learn.org/stable/modules/generated/sklearn.utils.check_array.html
    2025-07-17 15:32
      116.3K bytes
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  6. DecisionBoundaryDisplay — scikit-learn 1.7.1 do...

    multiclass_colors = None , xlabel = None , ylabel = None , ax = None , **...plot_method = 'contourf' , ax = None , xlabel = None , ylabel = None...
    scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html
    2025-07-18 16:24
      154.7K bytes
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  7. StratifiedGroupKFold — scikit-learn 1.7.1 docum...

    ( n_splits = 5 , shuffle = False , random_state = None ) [source]...StratifiedGroupKFold(n_splits=3, random_state=None, shuffle=False) >>> for i...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html
    2025-07-18 16:24
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  8. HashingVectorizer — scikit-learn 1.7.1 document...

    binary=False , norm='l2' , alternate_sign=True , dtype=<class..., input='content' , encoding='utf-8' , decode_error='strict'...
    scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.HashingVectorizer.html
    2025-07-18 16:24
      144.7K bytes
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  9. SGDRegressor — scikit-learn 1.7.1 documentation

    tol = 0.001 , shuffle = True , verbose = 0 , epsilon = 0.1 , random_state...( loss = 'squared_error' , * , penalty = 'l2' , alpha = 0.0001...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDRegressor.html
    2025-07-18 16:24
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  10. spectral_clustering — scikit-learn 1.7.1 docume...

    n_clusters = 8 , n_components = None , eigen_solver = None , random_state...random_state = None , n_init = 10 , eigen_tol = 'auto' , assign_labels...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.spectral_clustering.html
    2025-07-18 16:24
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