An Efficient Extreme Learning Machine Based on Fuzzy Information Granulation

Yuehua Gao, Tianyi Chen


In order to improve learning efficiency and generalization ability of extreme learning machine (ELM), an efficient extreme learning machine based on fuzzy information granulation (FIG) is put forward. The new approach not only improves the speed of basic ELM algorithm that contains many hidden nodes, but also overcomes the weakness of basic ELM of low learning efficiency and generalization ability by getting rid of redundant information in the observed values. The experimental results show that the proposed method is effective and can produce desirable generalization performance in most cases based on a few regression and classification problem.

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Copyright (c) 2017 Yuehua Gao, Tianyi Chen

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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