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Monotonic Constraints — scikit-learn 1.6.0 docu...
monotonic_cst = { "f_0" : 1 , "f_1" : - 1 } ) . fit ( X_df , y )...) f_1 = rng . rand ( n_samples ) X = np . c_ [ f_0 , f_1 ] noise...scikit-learn.org/stable/auto_examples/ensemble/plot_monotonic_constraints.html -
Roadmap — scikit-learn 1.6.0 documentation
cross-version safety from version 1.0. Note: Gael and Olivier think...scikit-learn.org/stable/roadmap.html -
「あ」から始まるタレント名一覧 1,184件中 1件から30件 - gooランキング
抑えて1位に選ばれたのは… 一番おいしい「エナジードリンク」ランキング！レッドブル、モンスターエナジーを抑えて1位に選ばれたのは…...DAIGO＆北川景子、1位は… #gooranking件のツイート 人気ランキング 24時間 週間 月間 1 【2024年最新...ranking.goo.ne.jp/talent/ -
Release History — scikit-learn 1.6.0 documentation
Version 1.1 Version 1.1.3 Version 1.1.2 Version 1.1.1 Version 1.1.0...Version 1.4.0 Version 1.3 Version 1.3.2 Version 1.3.1 Version 1.3.0...scikit-learn.org/stable/whats_new.html -
completeness_score — scikit-learn 1.6.0 documen...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) np.float64(1.0) Non-perfect...completeness_score ([ 0 , 0 , 1 , 1 ], [ 0 , 1 , 0 , 1 ])) 0.0 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.completeness_score.html -
precision_score — scikit-learn 1.6.0 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> precision_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html -
confusion_matrix — scikit-learn 1.6.0 documenta...
1 , 0 , 1 ], [ 1 , 1 , 1 , 0 ]) . ravel ()...negatives is \(C_{1,0}\) , true positives is \(C_{1,1}\) and false...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
sparse_encode — scikit-learn 1.6.0 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.sparse_encode.html -
Decision Tree Regression — scikit-learn 1.6.0 d...
scatter ( y_1 [:, 0 ], y_1 [:, 1 ], c = "cornflowerblue"...RandomState ( 1 ) X = np . sort ( 5 * rng . rand ( 80 , 1 ), axis =...scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html -
polynomial_kernel — scikit-learn 1.6.0 document...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>..., degree = 2 ) array([[1. , 1. ], [1.77..., 2.77...]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.polynomial_kernel.html