A New Kernel Extreme Learning Machine Framework for Somatization Disorder Diagnosis

A New Kernel Extreme Learning Machine Framework for Somatization Disorder Diagnosis

In this paper, we present a novel predictive model based on the kernel extreme learning machine (KELM) to predict the somatization disorder. Since the classification performance of KELM is largely affected by its two parameters, it is necessary to set two optimal parameters for it to ensure high pre...

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Bibliographic Details
Main Authors: Jie Luo, Huiling Chen, Zhongyi Hu, Hui Huang, Pengjun Wang, Xianqin Wang, Xin-En Lv, Congcong Wen
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Grey wolf optimization
moth-flame optimization
kernel extreme learning machine
somatization disorder diagnosis
Online Access:https://ieeexplore.ieee.org/document/8651566/

Internet

https://ieeexplore.ieee.org/document/8651566/

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