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  1. Non-negative least squares — scikit-learn 1.7.2...

    In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...
    scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html
    Wed Sep 24 16:15:25 UTC 2025
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  2. sklearn.linear_model — scikit-learn 1.7.2 docum...

    A variety of linear models. User guide. See the Linear Models section for further details. The following subsections are only rough guidelines: the same estimator can fall into multiple categories,...
    scikit-learn.org/stable/api/sklearn.linear_model.html
    Wed Sep 24 16:15:25 UTC 2025
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  3. clear_data_home — scikit-learn 1.7.2 documentation

    Skip to main content Back to top Ctrl + K GitHub Choose version clear_data_home # sklearn.datasets. clear_data_home (...
    scikit-learn.org/stable/modules/generated/sklearn.datasets.clear_data_home.html
    Wed Sep 24 16:15:24 UTC 2025
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  4. sklearn.cross_decomposition — scikit-learn 1.7....

    Algorithms for cross decomposition. User guide. See the Cross decomposition section for further details.
    scikit-learn.org/stable/api/sklearn.cross_decomposition.html
    Wed Sep 24 16:15:24 UTC 2025
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  5. Product — scikit-learn 1.7.2 documentation

    takes two kernels \(k_1\) and \(k_2\) and combines them via \[k_{prod}(X,...\[k_{prod}(X, Y) = k_1(X, Y) * k_2(X, Y)\] Note that the __mul__ magic...
    scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html
    Wed Sep 24 16:15:25 UTC 2025
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  6. API Reference — scikit-learn 1.7.2 documentation

    make_friedman2 Generate the “Friedman #2” regression problem. sklearn.datasets...sklearn.datasets make_hastie_10_2 Generate data for binary classification...
    scikit-learn.org/stable/api/index.html
    Wed Sep 24 16:15:25 UTC 2025
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  7. 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
    Wed Sep 24 16:15:26 UTC 2025
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  8. trustworthiness — scikit-learn 1.7.2 documentation

    defined as \[T(k) = 1 - \frac{2}{nk (2n - 3k - 1)} \sum^n_{i=1}...Should be fewer than n_samples / 2 to ensure the trustworthiness...
    scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html
    Wed Sep 24 16:15:25 UTC 2025
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  9. Permutation Importance with Multicollinear or C...

    n_jobs = 2 ) perm_sorted_idx = result . importances_mean...score ( X_test , y_test ) : .2 } " ) Baseline accuracy on test...
    scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance_multicollinear.html
    Wed Sep 24 16:15:25 UTC 2025
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  10. Column Transformer with Heterogeneous Data Sour...

    We will only use posts from 2 categories to speed up running...empty ( shape = ( len ( posts ), 2 ), dtype = object ) for i , text...
    scikit-learn.org/stable/auto_examples/compose/plot_column_transformer.html
    Wed Sep 24 16:15:25 UTC 2025
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