Comparison between extreme learning machine and wavelet neural networks in data classification

Siwar Yahia; Salwa Said; Olfa Jemai; Mourad Zaied; Chokri Ben Amar

doi:10.1117/12.2268648

17 March 2017 Comparison between extreme learning machine and wavelet neural networks in data classification

Siwar Yahia, Salwa Said, Olfa Jemai, Mourad Zaied, Chokri Ben Amar

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 103412K (2017) https://doi.org/10.1117/12.2268648
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

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.

Citation Download Citation

Siwar Yahia, Salwa Said, Olfa Jemai, Mourad Zaied, and Chokri Ben Amar "Comparison between extreme learning machine and wavelet neural networks in data classification", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103412K (17 March 2017); https://doi.org/10.1117/12.2268648

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