An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach

DOI10.1155/2014/985789zbMath1423.92102OpenAlexW2005025163WikidataQ30423403 ScholiaQ30423403MaRDI QIDQ2330194

Xuehua Zhao, Chao Ma, Jihong Ouyang, Hui ling Chen

Publication date: 21 October 2019

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/985789

zbMATH Keywords

subtractive clusteringkernel-based extreme learning machineParkinson's disease diagnosis system

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Medical applications (general) (92C50) Computational methods for problems pertaining to biology (92-08)

Uses Software

• LIBSVM

Cites Work

• Unnamed Item
• Evolutionary extreme learning machine
• Classification of Parkinson's disease using feature weighting method on the basis of fuzzy C-means clustering

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