Search Options

Results per page
Sort
Preferred Languages
Labels
Advance

Results 41 - 50 of 196 for v (0.04 sec)

  1. sklearn.linear_model.LassoLarsIC — 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.LassoLarsIC.html
    Sat May 11 22:20:02 UTC 2024
      58.4K bytes
      Cache
     
  2. About us — scikit-learn 1.4.2 documentation

    V . and Thirion , B . and Grisel...and Weiss , R . and Dubourg , V . and Vanderplas , J . and Passos...
    scikit-learn.org/stable/about.html
    Sat May 11 22:20:02 UTC 2024
      48.7K bytes
      Cache
     
  3. sklearn.metrics.normalized_mutual_info_score — ...

    See also v_measure_score V-Measure (NMI with arithmetic...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.normalized_mutual_info_score.html
    Sat May 11 22:20:02 UTC 2024
      22.3K bytes
      Cache
     
  4. sklearn.linear_model.Ridge — scikit-learn 1.4.2...

    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.Ridge.html
    Sat May 11 22:20:02 UTC 2024
      64.5K bytes
      Cache
     
  5. sklearn.isotonic.IsotonicRegression — 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.isotonic.IsotonicRegression.html
    Sat May 11 22:20:00 UTC 2024
      71.5K bytes
      Cache
     
  6. sklearn.multioutput.MultiOutputRegressor — scik...

    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.multioutput.MultiOutputRegressor.html
    Sat May 11 22:20:02 UTC 2024
      60.2K bytes
      Cache
     
  7. sklearn.svm.NuSVR — scikit-learn 1.4.2 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.svm.NuSVR.html
    Sat May 11 22:20:02 UTC 2024
      55.8K bytes
      Cache
     
  8. 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 11 22:20:02 UTC 2024
      73.5K bytes
      Cache
     
  9. decomposition.rst.txt

    V^*) = \underset{U, V}{\operatorname{arg\,min\,}}...multiply it with :math:`V_k`: .. math:: X' = X V_k .. note:: Most treatments...
    scikit-learn.org/stable/_sources/modules/decomposition.rst.txt
    Sat May 11 22:20:00 UTC 2024
      45.8K bytes
     
  10. 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 11 22:20:02 UTC 2024
      62.5K bytes
      Cache
     
Back to top