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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 -
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 -
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 -
1.2. Linear and Quadratic Discriminant Analysis...
X_k^tX_k = \frac{1}{n - 1} V S^2 V^t\) where \(V\) comes from the SVD...(centered) matrix: \(X_k = U S V^t\) . It turns out that we can...scikit-learn.org/stable/modules/lda_qda.html -
sklearn.base.RegressorMixin — 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.base.RegressorMixin.html -
sklearn.linear_model.LinearRegression — 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.LinearRegression.html -
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.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 -
sklearn.ensemble.VotingRegressor — 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.ensemble.VotingRegressor.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