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theme.min.css
1 3.6-8.1 8.1s3.6 8.1 8.1 8.1 8.1-3.6 8.1-8.1-3.6-8.1-8.1-8.1zM2.5...0-8.1 3.6-8.1 8.1s3.6 8.1 8.1 8.1 8.1-3.6 8.1-8.1-3.6-8.1-8.1-8.1zM2.5...fess.codelibs.org/_static/assets/css/theme.min.css -
dict-16.png
alpha=8 RGB 8 8 8 8 5271 1 1.0 1 8 8 8 8 true true 1015 Normal...fess.codelibs.org/ja/_images/dict-16.png -
Man United wins the FA Cup after stunning Man C...
defending champion Manchester City 2-1 in the final at Wembley on Saturday....last year’s which City won 2-1, and Pep Guardiola’s team did...www.nbcnews.com/news/sports/man-united-wins-fa-cup-stunning-man-city-2-1-final-rcna154063 -
1.4. Support Vector Machines — scikit-learn 1.5...
“0 vs 1”, “0 vs 2” , … “0 vs n”, “1 vs 2”, “1 vs 3”, “1 vs n”,...vectors \(v^{0}_1, v^{1}_1\) and \(v^{0}_2, v^{1}_2\) respectively....scikit-learn.org/stable/modules/svm.html -
ShuffleSplit — scikit-learn 1.5.0 documentation
array ([ 1 , 2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Train: index=[1 3 0 4] Test: index=[5 2] Fold 1: Train: index=[4...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
SparseCoder — scikit-learn 1.5.0 documentation
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...scikit-learn.org/stable/modules/generated/sklearn.decomposition.SparseCoder.html -
StratifiedShuffleSplit — scikit-learn 1.5.0 doc...
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [...np . array ([ 0 , 0 , 0 , 1 , 1 , 1 ]) >>> sss = StratifiedShuffleSpl...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html -
PowerTransformer — scikit-learn 1.5.0 documenta...
[[-1.316... -0.707...] [ 0.209... -0.707...] [ 1.106... 1.414...]]...X_trans * lambda_ + 1 ) ** ( 1 / lambda_ ) - 1 elif X < 0 and lambda_...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
ClassifierMixin — scikit-learn 1.5.0 documentation
predict ( X ) array([1, 1, 1]) >>> estimator . score ( X...MyEstimator ( param = 1 ) >>> X = np . array ([[ 1 , 2 ], [ 2 , 3 ],...scikit-learn.org/stable/modules/generated/sklearn.base.ClassifierMixin.html -
RepeatedStratifiedKFold — scikit-learn 1.5.0 do...
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...>>> y = np . array ([ 0 , 0 , 1 , 1 ]) >>> rskf = RepeatedStratifiedKF...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedStratifiedKFold.html
