Adapted B-CUBED Metrics to Unbalanced Datasets
Résumé
B-CUBED metrics have been recently adopted in the evaluation of clustering results as well as in many other related tasks. However, these families of metrics are not well adapted when datasets are unbalanced. This issue is extremely frequent in Web results, where classes are distributed following a strong unbalanced pattern. In that order, we present a modified version of B-CUBED metrics to overcome this situation. Results in toy and real datasets indicate that the proposed adaptation correctly consider the particularities of the unbalanced datasets.