Colour me surprised when the `r2_score` implementation in sklearn returned negative scores. What gives? R² is defined upon the basis that the total sum of squares of a fitted model is equal to the…
{'n_folds': 4, 'n_repeats': 2, 'strategy': 'stratified_sklearn'} scores = {'acc': 0.9, 'spec': 0.9, 'sens': 0.6, 'bacc': 0.1, 'f1': 0.95} result = check_1_dataset_known_folds_mos( dataset=dataset, folding=folding, fold_score_bounds={'acc': (0.8, 1.0)}, scores=...
The Mean Square Error returned by sklearn.cross_validation.cross_val_score is always a negative. While being a designed decision so that the output of this function can be used for maximization given some hyperparameters, it's extremely ...
For this dataset, the classes that had the lowest detection rates were R2L and U2R, so we report the following performance metrics specifically for these two classes: precision, recall, and F1 score. For the NSL-KDD multiclass experiments, the detailed results of those metrics are in Table ...