B-ROC Curves for the Assessment of Classifiers over Imbalanced Data Sets

B-ROC Curves for the Assessment of Classifiers over Imbalanced Data Sets

Title : B-ROC Curves for the Assessment of Classifiers over Imbalanced Data Sets
Authors :
Cardenas, Alvaro A
Baras, John, S.
Conference : 21st National Conference on Artificial Intelligence pp. 1581-1584
Date: July 16 - July 20, 2006

The class imbalance problem appears to be ubiquitous to a large portion of the machine learning and data mining communities. One of the key questions in this setting is how to evaluate the learning algorithms in the case of class imbalances. In this paper we introduce the Bayesian Receiver Operating Characteristic (B-ROC) curves, as a set of tradeoff curves that combine in an intuitive way, the variables that are more relevant to the evaluation of classifiers over imbalanced data sets. This presentation is based on section 4 of (CĀ“ardenas, Baras, & Seamon 2006).

Download Full Paper