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Results 41 - 50 of 266 for v (0.07 sec)

  1. TheilSenRegressor — scikit-learn 1.7.1 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.linear_model.TheilSenRegressor.html
    Thu Aug 28 22:04:19 UTC 2025
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  2. 2.5. Decomposing signals in components (matrix ...

    V^*) = \underset{U, V}{\operatorname{arg\,min\,}}...we multiply it with \(V_k\) : \[X' = X V_k\] Note Most treatments...
    scikit-learn.org/stable/modules/decomposition.html
    Thu Aug 28 22:04:19 UTC 2025
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  3. IsotonicRegression — scikit-learn 1.7.1 documen...

    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.isotonic.IsotonicRegression.html
    Thu Aug 28 22:04:19 UTC 2025
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  4. VotingRegressor — scikit-learn 1.7.1 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.ensemble.VotingRegressor.html
    Thu Aug 28 22:04:16 UTC 2025
      146.4K bytes
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  5. normalized_mutual_info_score — scikit-learn 1.7...

    See also v_measure_score V-Measure (NMI with arithmetic...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.normalized_mutual_info_score.html
    Thu Aug 28 22:04:16 UTC 2025
      112.4K bytes
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  6. LinearRegression — scikit-learn 1.7.1 documenta...

    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.LinearRegression.html
    Thu Aug 28 22:04:19 UTC 2025
      151.4K bytes
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  7. PLSCanonical — scikit-learn 1.7.1 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.cross_decomposition.PLSCanonical.html
    Thu Aug 28 22:04:19 UTC 2025
      159.2K bytes
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  8. LassoLarsIC — scikit-learn 1.7.1 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.LassoLarsIC.html
    Thu Aug 28 22:04:19 UTC 2025
      145.7K bytes
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  9. KNeighborsRegressor — scikit-learn 1.7.1 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.neighbors.KNeighborsRegressor.html
    Thu Aug 28 22:04:16 UTC 2025
      151.8K bytes
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  10. ARDRegression — scikit-learn 1.7.1 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
    Thu Aug 28 22:04:19 UTC 2025
      141.3K bytes
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