Classification approach based on association rules mining for unbalanced data

This paper deals with the supervised classification when the response variable is binary and its class distribution is unbalanced. In such situation, it is not possible to build a powerful classifier by using standard methods such as logistic regression, classification tree, discriminant analysis, etc. To overcome this shortcoming of these methods that… CONTINUE READING