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sklearn.metrics.homogeneity_score — scikit-lear...
v_measure_score V-Measure (NMI with arithmetic...Rosenberg and Julia Hirschberg, 2007. V-Measure: A conditional entropy-based...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
sklearn.decomposition.MiniBatchDictionaryLearni...
V ^* ) = argmin 0.5 || X - U V || _Fro ^ 2 + alpha...* || U || _1 , 1 ( U , V ) with || V_k || _2 <= 1 for all 0 <=...scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchDictionaryLearning.html -
feature_extraction.rst.txt
:math:`v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...:math:`v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
sklearn.linear_model.QuantileRegressor — scikit...
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.QuantileRegressor.html -
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 -
sklearn.compose.TransformedTargetRegressor — sc...
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.compose.TransformedTargetRegressor.html -
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 -
sklearn.linear_model.RidgeCV — 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.RidgeCV.html -
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 -
sklearn.linear_model.OrthogonalMatchingPursuit ...
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.OrthogonalMatchingPursuit.html