We propose a classification method based on a decision tree whose nodes consist of linear Support Vector Machines (SVMs). Each node defines a decision hyperplane that classifies p...
Recently, the area of rule extraction from support vector machines (SVMs) has been explored. One important indication of the success of a rule extraction method is the performance...
A two-class imbalanced data problem (IDP) emerges when the data from majority class are compactly clustered and the data from minority class are scattered. Though a discriminative...
Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computation...
Today's communication-based applications are mostly crafted in a stovepipe development paradigm, which is inflexible to be used by various domain-specific applications and cos...