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AdaBoostRegressor — scikit-learn 1.7.2 document...
predict ([[ 0 , 0 , 0 , 0 ]]) array([4.7972]) >>> regr . score ( X ,...{‘linear’, ‘square’, ‘exponential’}, default=’linear’ The loss function...scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostRegressor.html -
normalized_mutual_info_score — scikit-learn 1.7...
fo_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> norm...fo_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 If classes...scikit-learn.org/stable/modules/generated/sklearn.metrics.normalized_mutual_info_score.html -
cross_val_predict — scikit-learn 1.7.2 document...
instead. E.g.: cross_val_predict(..., params={'groups': groups})...‘2*n_jobs’ method {‘predict’, ‘predict_proba’, ‘predict_log_proba’,...scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_predict.html -
mutual_info_score — scikit-learn 1.7.2 document...
= [ 0 , 1 , 1 , 0 , 1 , 0 ] >>> labels_pred = [ 0 , 1 , 0 , 0...switching \(U\) (i.e label_true ) with \(V\) (i.e. label_pred ) will...scikit-learn.org/stable/modules/generated/sklearn.metrics.mutual_info_score.html -
Pipeline — scikit-learn 1.7.2 documentation
'scaler' , StandardScaler ()), ( 'svc' , SVC ())]) >>> # The...train_test_split ( X , y , ... random_state = 0 ) >>> pipe = Pipeline ([( 'scaler'...scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html -
RandomForestRegressor — scikit-learn 1.7.2 docu...
“absolute_error”, “friedman_mse”, “poisson”}, default=”squared_error” The...changed from 10 to 100 in 0.22. criterion {“squared_error”, “absolute_error”,...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html -
MaxAbsScaler — scikit-learn 1.7.2 documentation
2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , - 1. ]] >>> transformer...transformer . transform ( X ) array([[ 0.5, -1. , 1. ], [ 1. , 0. , 0....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
SimpleImputer — scikit-learn 1.7.2 documentation
transform ( X )) [[ 7. 2. 3. ] [ 4. 3.5 6. ] [10. 3.5 9. ]] For...imp_mean . fit ([[ 7 , 2 , 3 ], [ 4 , np . nan , 6 ], [ 10 , 5 , 9...scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html -
MLPClassifier — scikit-learn 1.7.2 documentation
function, returns f(x) = 1 / (1 + exp(-x)). ‘tanh’, the hyperbolic tan...function, returns f(x) = max(0, x) solver {‘lbfgs’, ‘sgd’, ‘adam’},...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html -
RocCurveDisplay — scikit-learn 1.7.2 documentation
0.1 , 0.4 , 0.35 , 0.8 ]) >>> fpr , tpr , thresholds = metrics...np . array ([ 0 , 0 , 1 , 1 ]) >>> y_score = np . array ([ 0.1...scikit-learn.org/stable/modules/generated/sklearn.metrics.RocCurveDisplay.html