Learning ELM network weights using linear discriminant analysis
Neural and Evolutionary Computing
2014-06-13 v1 Machine Learning
Machine Learning
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.
Cite
@article{arxiv.1406.3100,
title = {Learning ELM network weights using linear discriminant analysis},
author = {Philip de Chazal and Jonathan Tapson and André van Schaik},
journal= {arXiv preprint arXiv:1406.3100},
year = {2014}
}
Comments
In submission to the ELM 2014 conference