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MinMaxScaler — scikit-learn 1.7.2 documentation
transform ([[ 2 , 2 ]])) [[1.5 0. ]] fit ( X , y...MinMaxScaler >>> data = [[ - 1 , 2 ], [ - 0.5 , 6 ], [ 0 , 10 ],...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html -
roc_curve — scikit-learn 1.7.2 documentation
2 , 2 ]) >>> scores = np . array ([...Returns : fpr ndarray of shape (>2,) Increasing false positive rates...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html -
PLSRegression — scikit-learn 1.7.2 documentation
[ 2. , 2. , 2. ], [ 2. , 5. , 4. ]] >>> y =...= [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 , 12.3...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSRegression.html -
rand_score — scikit-learn 1.7.2 documentation
of Classification 2, 193–218 (1985). . [ 2 ] Wikipedia: Simple...predicted and true clusterings [1] [2] . The raw RI score [3] is: RI...scikit-learn.org/stable/modules/generated/sklearn.metrics.rand_score.html -
top_k_accuracy_score — scikit-learn 1.7.2 docum...
2 , 2 ]) >>> y_score = np . array ([[ 0.5 , 0.2 , 0.2 ], #...top 2 ... [ 0.3 , 0.4 , 0.2 ], # 1 is in top 2 ... [ 0.2 , 0.4...scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html -
SGD: Maximum margin separating hyperplane — sci...
centers = 2 , random_state = 0 , cluster_std...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html -
APM Server version 6.2 | APM Server Reference [...
2.3 APM Server version 6.2.2 APM Server version 6.2.1 APM...Server version 6.2 View commits APM Server version 6.2.4 APM Server...www.elastic.co/guide/en/apm/server/current/release-notes-6.2.html -
Servidor de Búsqueda de Texto Completo de Códig...
2.0 2025-07-20 Lanzamiento de Fess...2025-05-24 Lanzamiento de Fess 14.19.2 2025-03-02 Lanzamiento de Fess...fess.codelibs.org/es/news.html -
Plot the decision surfaces of ensembles of tree...
2 , w_pad = 0.2 , pad = 2.5 ) plt . show ()...pair in ([ 0 , 1 ], [ 0 , 2 ], [ 2 , 3 ]): for model in models...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_iris.html -
7.5. Unsupervised dimensionality reduction — sc...
2. Random projections # The module:...scikit-learn.org/stable/modules/unsupervised_reduction.html