A Fuzzy Adaptive Binary Global Learning Colonization-MLP model for Body Fat Prediction

Title
A Fuzzy Adaptive Binary Global Learning Colonization-MLP model for Body Fat Prediction
Publication Date
2019
Author(s)
Keivanian, Farshid
Chiong, Raymond
( author )
OrcID: https://orcid.org/0000-0002-8285-1903
Email: rchiong@une.edu.au
UNE Id une-id:rchiong
Hu, Zhongyi
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
IEEE
Place of publication
United States of America
DOI
10.1109/BIOSMART.2019.8734215
UNE publication id
une:1959.11/61420
Abstract

Body fat prediction is a step toward addressing obesity issues. In this paper, we propose a machine learning-based prediction model incorporating a novel fuzzy adaptive global learning binary colonization method for feature selection. Two fuzzy inference systems are used to select input features more purposefully. The proposed model is validated against several well-known feature selection-based models. Experimental results show that it is able to outperform the other models in comparison on most of the performance metrics considered.

Link
Citation
Proceedings of the 3rd International Conference on Bio-Engineering for Smart Technologies, p. 1-4
ISBN
9781728135786
9781728135779
9781728135793
Start page
1
End page
4

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