Extreme Learning Machines with Simple Cascades

Tom Gedeon, Anthony Oakden

2015

Abstract

We compare extreme learning machines with cascade correlation on a standard benchmark dataset for comparing cascade networks along with another commonly used dataset. We introduce a number of hybrid cascade extreme learning machine topologies ranging from simple shallow cascade ELM networks to full cascade ELM networks. We found that the simplest cascade topology provided surprising benefit with a cascade correlation style cascade for small extreme learning machine layers. Our full cascade ELM architecture achieved high performance with even a single neuron per ELM cascade, suggesting that our approach may have general utility, though further work needs to be done using more datasets. We suggest extensions of our cascade ELM approach, with the use of network analysis, addition of noise, and unfreezing of weights.

Paper Citation

in Harvard Style

Gedeon T. and Oakden A. (2015). Extreme Learning Machines with Simple Cascades . In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-120-5, pages 271-278. DOI: 10.5220/0005539502710278

in Bibtex Style

@conference{simultech15,
author={Tom Gedeon and Anthony Oakden},
title={Extreme Learning Machines with Simple Cascades},
booktitle={Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2015},
pages={271-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005539502710278},
isbn={978-989-758-120-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Extreme Learning Machines with Simple Cascades
SN - 978-989-758-120-5
AU - Gedeon T.
AU - Oakden A.
PY - 2015
SP - 271
EP - 278
DO - 10.5220/0005539502710278