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  1. sklearn.cross_decomposition.CCA — scikit-learn ...

    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.cross_decomposition.CCA.html
    Sat May 18 15:26:01 UTC 2024
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  2. sklearn.linear_model.ARDRegression — scikit-lea...

    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
    Sat May 18 15:26:00 UTC 2024
      54.7K bytes
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  3. sklearn.linear_model.ElasticNet — scikit-learn ...

    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
    Sat May 18 15:26:01 UTC 2024
      77.6K bytes
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  4. sklearn.linear_model.LassoCV — scikit-learn 1.4...

    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
    Sat May 18 15:26:01 UTC 2024
      80.3K bytes
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  5. sklearn.kernel_ridge.KernelRidge — scikit-learn...

    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
    Sat May 18 15:26:01 UTC 2024
      54.8K bytes
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  6. sklearn.linear_model.OrthogonalMatchingPursuitC...

    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.OrthogonalMatchingPursuitCV.html
    Sat May 18 15:26:00 UTC 2024
      49.8K bytes
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  7. sklearn.neural_network.MLPRegressor — scikit-le...

    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.neural_network.MLPRegressor.html
    Sat May 18 15:26:00 UTC 2024
      62.5K bytes
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  8. sklearn.linear_model.LassoLarsCV — scikit-learn...

    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
    Sat May 18 15:26:00 UTC 2024
      58.5K bytes
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  9. sklearn.ensemble.ExtraTreesRegressor — scikit-l...

    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
    Sat May 18 15:26:00 UTC 2024
      77.8K bytes
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  10. sklearn.dummy.DummyRegressor — scikit-learn 1.4...

    coefficient R^2 is defined as (1 - u/v) , where u is the residual sum...((y_true - y_pred) ** 2).sum() and v is the total sum of squares ((y_true...
    scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyRegressor.html
    Sat May 18 15:26:00 UTC 2024
      52.7K bytes
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