in this article, a multi-objective memetic algorithm (ma) for rule learning is proposed. prediction accuracy and interpretation are two measures that conflict with each other. in this approach, we consider accuracy and interpretation of rules sets. additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. this...

Support vector machine has a better classification and prediction performance on balance data classification, but has a poor performance for imbalance data. In this paper, the reason of the poor results which were produced by imbalance data is explained. And a new approach is proposed to solve the imbalance data classification. By this method the imbalance data problem is converted to several i...

Class imbalance exists in many data domains, posing numerous challenges to the research community. Medical datasets, most cases are predominantly imbalanced nature. Through tackling multi-class issues, researchers preferred conventional method of decomposing it into binary classes for a more convenient solution. This is not applicable solving sensitive and crucial such as medical data. Classify...