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clustering.rst.txt
for :math:`V`: .. math:: H(V) = - \sum_{j=1}^{|V|}P'(j)\log(P'(j))...\frac{|U_i \cap V_j|}{N}\log\left(\frac{N|U_i \cap V_j|}{|U_i||V_j|}\right)...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
2.4. Biclustering — scikit-learn 1.7.2 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 -
completeness_score — scikit-learn 1.7.2 documen...
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.completeness_score.html -
Government shutdown live updates: Day 3 of fede...
remarks on the landmark Obergefell v. Hodges ruling, in which he dissented,...Alexandra Marquez Frank Thorp V producer and off-air reporter...www.nbcnews.com/politics/trump-administration/live-blog/government-shutdown-trump-layoffs-federal... -
7.2. Feature extraction — scikit-learn 1.7.2 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 -
1.8. Cross decomposition — scikit-learn 1.7.2 d...
using the rotation matrix \(V(\Delta^T V)^{-1}\) , accessed via the...to compute \(u_k\) and \(v_k\) , \(v_k\) is never normalized....scikit-learn.org/stable/modules/cross_decomposition.html -
homogeneity_score — scikit-learn 1.7.2 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 -
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 -
Bunch — scikit-learn 1.7.2 documentation
v in E: D[k] = v In either case, this is...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html