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OneToOneFeatureMixin — scikit-learn 1.7.1 docum...
generated: ["x0", "x1", ..., "x(n_features_in_ - 1)"] . If input_features...get_feature_names_out () array(['x0', 'x1'], dtype=object) get_feature_names_out...scikit-learn.org/stable/modules/generated/sklearn.base.OneToOneFeatureMixin.html -
ClassifierTags — scikit-learn 1.7.1 documentation
accuracy of 0.83 on make_blobs(n_samples=300, random_state=0) . The datasets...sklearn.utils. ClassifierTags ( poor_score : bool = False , multi_class...scikit-learn.org/stable/modules/generated/sklearn.utils.ClassifierTags.html -
Custom refit strategy of a grid search with cro...
predict. Parameters ---------- cv_results : dict of numpy (masked)...digits . images . reshape (( n_samples , - 1 )) y = digits . target...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_digits.html -
Ordinary Least Squares and Ridge Regression — s...
"Target" , title = "Train set" ) ax [ 0 ] . legend () ax [ 1 ] . scatter...predictions" , ) ax [ 0 ] . set ( xlabel = "Feature" , ylabel = "Target"...scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge.html -
Plotting Cross-Validated Predictions — scikit-l...
cross_val_predict ( lr , X , y , cv = 10 ) Since cv=10 , it means that...) axs [ 0 ] . set_title ( "Actual vs. Predicted values" ) PredictionErrorDispl...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html -
model_evaluation.rst.txt
evaluation (`mean_pinball_loss(..., alpha=0.99)` - we apologize...Association 102 (2007), pp. 359– 378. `link to pdf <https://sites.sta...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
PrecisionRecallDisplay — scikit-learn 1.7.1 doc...
train_test_split ( X , y , ... random_state = 0 ) >>> clf = SVC ( random_state...precision , recall = recall ) >>> disp . plot () <...> >>> plt . show...scikit-learn.org/stable/modules/generated/sklearn.metrics.PrecisionRecallDisplay.html -
classification_report — scikit-learn 1.7.1 docu...
{ 'precision' : 0.5 , 'recall' : 1.0 , 'f1-score' : 0.67 , 'support'...recall f1-score support class 0 0.50 1.00 0.67 1 class 1 0.00 0.00...scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html -
r2_score — scikit-learn 1.7.1 documentation
948... >>> y_true = [[ 0.5 , 1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>>...[ 2.5 , 0.0 , 2 , 8 ] >>> r2_score ( y_true , y_pred ) 0.948......scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
log_loss — scikit-learn 1.7.1 documentation
log_loss ([ "spam" , "ham" , "ham" , "spam" ], ... [[ .1 , .9 ], [...[ .9 , .1 ], [ .8 , .2 ], [ .35 , .65 ]]) 0.21616 Gallery examples...scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html