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Decomposition — scikit-learn 1.7.2 documentation
Factor Analysis (FA) Principal Component Analysis (PCA) on Iris Dataset...top Ctrl + K GitHub Choose version Decomposition # Examples concerning...scikit-learn.org/stable/auto_examples/decomposition/index.html -
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color: #000 } /* Other */ html[data-theme="light"] .highlight .p {..."] .highlight .n { color: #000 } /* Name */ html[data-theme="light"]...scikit-learn.org/stable/_static/pygments.css -
adjusted_mutual_info_score — scikit-learn 1.7.2...
adjusted_mutual_info_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> adju...adjusted_mutual_info_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 If classes...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_mutual_info_score.html -
8.4. Loading other datasets — scikit-learn 1.7....
'c-CS-s', 'c-SC-m', 'c-SC-s', 't-CS-m', 't-CS-s', 't-SC-m', 't-SC-s'],...(1080,) >>> np . unique ( mice . target ) array(['c-CS-m', 'c-CS-s',...scikit-learn.org/stable/datasets/loading_other_datasets.html -
kneighbors_graph — scikit-learn 1.7.2 documenta...
True ) >>> A . toarray () array([[1., 0., 1.], [0., 1., 1.], [1.,...[1., 0., 1.]]) Gallery examples # Agglomerative clustering with...scikit-learn.org/stable/modules/generated/sklearn.neighbors.kneighbors_graph.html -
2.2. Manifold learning — scikit-learn 1.7.2 doc...
\log(N)] + O[N^2(k + \log(N))] + O[d N^2]\) . \(N\) : number of...embedding” Roweis, S. & Saul, L. Science 290:2323 (2000) 2.2.4. Modified...scikit-learn.org/stable/modules/manifold.html -
6. Visualizations — scikit-learn 1.7.2 document...
visualization. metrics.ConfusionMatrixDispl (...[, ...]) Confusion...visualization. metrics.DetCurveDisplay (*, fpr, fnr[, ...]) Detection...scikit-learn.org/stable/visualizations.html -
homogeneity_score — scikit-learn 1.7.2 document...
homogeneity_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 0 , 0 ])) 0.0... Gallery examples...homogeneity_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
8.3. Generated datasets — scikit-learn 1.7.2 do...
= 0 ) ax2 . scatter ( X [:, 0 ], X [:, 1 ], c = Y ) ax2 . set_title...random_state = 0 ) plt . scatter ( X [:, 0 ], X [:, 1 ], c = y ) plt ....scikit-learn.org/stable/datasets/sample_generators.html -
BisectingKMeans — scikit-learn 1.7.2 documentation
np . array ([[ 1 , 1 ], [ 10 , 1 ], [ 3 , 1 ], ... [ 10 , 0 ],...], [ 2 , 1 ], [ 10 , 2 ], ... [ 10 , 8 ], [ 10 , 9 ], [ 10 , 10...scikit-learn.org/stable/modules/generated/sklearn.cluster.BisectingKMeans.html