Learning ELM network weights using linear discriminant analysis

Abstract

We present an alternative to the pseudo-inverse method for determining the hidden to output weight values for Extreme Learning Machines performing classification tasks. The method is based on linear discriminant analysis and provides Bayes optimal single point estimates for the weight values.

In submission to the ELM 2014 conference