A Cost Sensitive Minimal Learning Machine for Pattern Classification

The present work proposes a variant of the Minimal Learning Machine (MLM) in a cost sensitiVe framework for classification. MLM is a recently proposed supervised learning algorithm with a simple formulation and few hyperparameters. The proposed method is tested under two classification problems: imbalanced classification and classification with reject option. The results are comparable to other to state of the art classifiers.