F1_Score—The weighted average of the precision and recall. Values range from 0 to 1 in which 1 means highest accuracy. AP—The Average Precision (AP) metric, which is the precision averaged across all recall values between 0 and 1 at a given Intersection over Union (IoU) value....
Methods include: ['accuracy', 'balanced_accuracy', 'precision', 'average_precision', 'brier', 'f1_score', 'mxe', 'recall', 'jaccard', 'roc_auc', 'mse', 'rmse', 'sar'] Rank correlation coefficients: rk.corr(r1, r2, method='spearman'). Methods include: ['kendalltau', 'spearman'...
This will generate an ROC plot and save the performance evaluations [precision, recall, f1-score, AUC, PRC] to Improse_tesults.txt. Make predictions To make predictions should have computed available features and saved a CSV file. Next, you need to tell the model the features you have to...
F1_Score—Moyenne pondérée de l’exactitude et du rappel. Les valeurs sont comprises entre 0 et 1, 1 indiquant la précision la plus élevée. AP—Mesure de l’exactitude moyenne, qui est l’exactitude moyenne calculée sur toutes les valeurs de rappel entre 0 et 1 à une valeur ...