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  1. LassoLars — scikit-learn 1.7.0 documentation

    is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLars.html
    Fri Jun 06 09:13:46 UTC 2025
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  2. CountVectorizer — scikit-learn 1.7.0 documentation

    2) means unigrams and bigrams, and (2, 2) means only...= 'word' , ngram_range = ( 2 , 2 )) >>> X2 = vectorizer2 . fit_transform...
    scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html
    Fri Jun 06 09:13:47 UTC 2025
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  3. Single estimator versus bagging: bias-variance ...

    - ( x ** 2 )) + 1.5 * np . exp ( - (( x - 2 ) ** 2 )) def generate...{0} : {1:.4f} (error) = {2:.4f} (bias^2) " " + {3:.4f} (var) +...
    scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html
    Fri Jun 06 09:13:47 UTC 2025
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  4. make_gaussian_quantiles — scikit-learn 1.7.0 do...

    int64(2), np.int64(0), np.int64(1), np.int64(0), np.int64(2)] Gallery...n_samples = 100 , n_features = 2 , n_classes = 3 , shuffle = True...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html
    Fri Jun 06 09:13:47 UTC 2025
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  5. make_friedman2 — scikit-learn 1.7.0 documentation

    0 ] ** 2 + ( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1...[source] # Generate the “Friedman #2” regression problem. This dataset...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html
    Fri Jun 06 09:13:47 UTC 2025
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  6. compute_optics_graph — scikit-learn 1.7.0 docum...

    2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8...samples (rounded to be at least 2). max_eps float, default=np.inf...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html
    Fri Jun 06 09:13:47 UTC 2025
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  7. plot_classifier_comparison.zip

    make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...
    scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip
    Fri Jun 06 09:13:47 UTC 2025
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  8. KNeighborsTransformer — scikit-learn 1.7.0 docu...

    array([[2]])) As you can see, it returns [[0.5]], and [[2]], which..., metric = 'minkowski' , p = 2 , metric_params = None , n_jobs...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html
    Fri Jun 06 09:13:46 UTC 2025
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  9. Selecting dimensionality reduction with Pipelin...

    ] ) N_FEATURES_OPTIONS = [ 2 , 4 , 8 ] C_OPTIONS = [ 1 , 10...'reduce_dim__n_components': [2, 4, 8]}, {'classify__C': [1, 10,...
    scikit-learn.org/stable/auto_examples/compose/plot_compare_reduction.html
    Fri Jun 06 09:13:47 UTC 2025
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  10. OrthogonalMatchingPursuit — scikit-learn 1.7.0 ...

    float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...coefficient of determination, \(R^2\) , is defined as \((1 - \frac{u}{v})\)...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuit.html
    Fri Jun 06 09:13:47 UTC 2025
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