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  1. ElasticNet — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html
    Mon Oct 20 15:12:26 UTC 2025
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  2. LassoCV — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html
    Mon Oct 20 15:12:26 UTC 2025
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  3. KernelRidge — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.kernel_ridge.KernelRidge.html
    Mon Oct 20 15:12:26 UTC 2025
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  4. ARDRegression — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.ARDRegression.html
    Mon Oct 20 15:12:26 UTC 2025
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  5. AdaBoostRegressor — scikit-learn 1.7.2 document...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostRegressor.html
    Mon Oct 20 15:12:25 UTC 2025
      144.8K bytes
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  6. HuberRegressor — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.HuberRegressor.html
    Mon Oct 20 15:12:25 UTC 2025
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  7. ExtraTreesRegressor — scikit-learn 1.7.2 docume...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesRegressor.html
    Mon Oct 20 15:12:26 UTC 2025
      162.1K bytes
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  8. about.rst.txt

    V. and Thirion, B. and Grisel, O....P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos,...
    scikit-learn.org/stable/_sources/about.rst.txt
    Mon Oct 20 15:12:27 UTC 2025
      18.2K bytes
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  9. DecisionTreeRegressor — scikit-learn 1.7.2 docu...

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html
    Mon Oct 20 15:12:25 UTC 2025
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  10. LassoLarsCV — scikit-learn 1.7.2 documentation

    is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsCV.html
    Mon Oct 20 15:12:24 UTC 2025
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