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2.4. Biclustering — scikit-learn 1.7.1 document...
\(u_2 \dots u_{p+1}\) and \(v_2 \dots v_{p+1}\) except in the case...decomposition, \(A_n = U \Sigma V^\top\) , provides the partitions...scikit-learn.org/stable/modules/biclustering.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 -
7.2. Feature extraction — scikit-learn 1.7.1 do...
norm: \(v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...norm: \(v_{norm} = \frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 +...scikit-learn.org/stable/modules/feature_extraction.html -
homogeneity_score — scikit-learn 1.7.1 document...
v_measure_score V-Measure (NMI with arithmetic...Rosenberg and Julia Hirschberg, 2007. V-Measure: A conditional entropy-based...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
1.2. Linear and Quadratic Discriminant Analysis...
X_k^tX_k = \frac{1}{n - 1} V S^2 V^t\) 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 -
Bunch — scikit-learn 1.7.1 documentation
v in E: D[k] = v In either case, this is...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
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 -
bootstrap.js
v=d.y,y=void 0===v?0:v,w="function"==typeof...d 0===_?u:_,v=i.elementContext,y=void 0===v?f:v,w=i.altBoundary,E=void...scikit-learn.org/stable/_static/scripts/bootstrap.js -
TransformedTargetRegressor — scikit-learn 1.7.1...
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 -
BernoulliRBM — scikit-learn 1.7.1 documentation
gibbs ( v ) [source] # Perform one Gibbs...Gibbs sampling step. Parameters : v ndarray of shape (n_samples, n_features)...scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html