Share Email Print
cover

Proceedings Paper

Comparison between extreme learning machine and wavelet neural networks in data classification
Author(s): Siwar Yahia; Salwa Said; Olfa Jemai; Mourad Zaied; Chokri Ben Amar
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Extreme learning Machine is a well known learning algorithm in the field of machine learning. It's about a feed forward neural network with a single-hidden layer. It is an extremely fast learning algorithm with good generalization performance. In this paper, we aim to compare the Extreme learning Machine with wavelet neural networks, which is a very used algorithm. We have used six benchmark data sets to evaluate each technique. These datasets Including Wisconsin Breast Cancer, Glass Identification, Ionosphere, Pima Indians Diabetes, Wine Recognition and Iris Plant. Experimental results have shown that both extreme learning machine and wavelet neural networks have reached good results.

Paper Details

Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103412K (17 March 2017); doi: 10.1117/12.2268648
Show Author Affiliations
Siwar Yahia, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Salwa Said, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Olfa Jemai, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Mourad Zaied, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Chokri Ben Amar, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)


Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top