2-Degree Polynomial Circular Extreme Learning Machine for Classification Problem

Authors

  • Sarutte Atsawaraungsuk Computer Education Department, Education Faculty, Udonthani Rajabhat University, Udonthani, Thailand.

Keywords:

Extreme Learning Machine, Polynomial, Circular Extreme Learning Machine,

Abstract

The Circular Extreme Learning Machine (CELM) is the combination of Extreme Learning Machine (ELM) and Circular Back Propagation (CBP). CELM uses the structure same as ELM to get speedy in the training process and gets benefit from CBP architecture by using the 2-degree polynomial to make the better performance. However, the using 2-degree polynomial of CELM can create the decided boundary shape similar as RBF that may be limited the distance, between the center point and the data by the sigmoid activation function. So that, a 2-degree Polynomial Circular Extreme Learning Machine (PCELM) is proposed to tackle this problem. Our experiment showed that PCELM outperformed the original ELM and the traditional CELM with several activation functions. Wilcoxon signed rank test was used to compare statistical differences between PCELM and the CELM that can confirm the PCELM can improve the performance of CELM.

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Published

2018-01-29

How to Cite

Atsawaraungsuk, S. (2018). 2-Degree Polynomial Circular Extreme Learning Machine for Classification Problem. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-4), 101–105. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3600

Issue

Vol. 10 No. 1-4: Breakthrough To Excellence in Communication and Computer Engineering I

Section

Articles

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