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completeness_score — scikit-learn 1.7.2 d...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect labelings...completeness_score ([ 0 , 0 , 1 , 1 ], [ 0 , 1 , 0 , 1 ])) 0.0 >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.completeness_score.html -
CountVectorizer — scikit-learn 1.7.2 docu...
[[0 1 1 1 0 0 1 0 1] [0 2 0 1 0 1 1 0 1] [1 0 0 1 1 0 1 1 1] [0...[[0 0 1 1 0 0 1 0 0 0 0 1 0] [0 1 0 1 0 1 0 1 0 0 1 0 0] [1 0 0...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
Version 1.7 — scikit-learn 1.7.2 document...
#31559 Version 1.7.1 # July 2025 sklearn.base # Fix...use n_init=1 by default, starting from version 1.9. By Dmitry...scikit-learn.org/stable/whats_new/v1.7.html -
brier_score_loss — scikit-learn 1.7.2 doc...
y_true in {-1, 1} or {0, 1}, pos_label defaults to 1; else if y_true...defined as: \[\frac{1}{N}\sum_{i=1}^{N}\sum_{c=1}^{C}(y_{ic} - \hat{p}_{ic})^{2}\]...scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html -
移行 1.0.4D to 1.0.4F | DBFlute
dbflute.seasar.org/ja/environment/upgrade/migration/migrate104Dto104F.html -
移行 1.0.4C to 1.0.4D | DBFlute
dbflute.seasar.org/ja/environment/upgrade/migration/migrate104Cto104D.html -
LabelBinarizer — scikit-learn 1.7.2 docum...
array([[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 1, 0]]) fit ( y )...fit ( np . array ([[ 0 , 1 , 1 ], [ 1 , 0 , 0 ]])) LabelBinarizer()...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelBinarizer.html -
precision_score — scikit-learn 1.7.2 docu...
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred...= [[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html -
DataAccessUtils (Spring Framework 7.0.1 API)
Since: 1.0.2 Author: Juergen Hoeller Constructor...throws an exception if more than 1 element found. Parameters: results...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/dao/support/DataAcce... -
NearestNeighbors — scikit-learn 1.7.2 doc...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) radius_neighbors...() array([[1., 0., 1.], [0., 1., 0.], [1., 0., 1.]]) set_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html