A Parallel Ensemble Fuzzy Classifier for Diabetes Diagnosis

Author:

Zhang Xiongtao,Jiang Yunliang,Hu Wenjun,Wang Shitong

Abstract

Diabetes is one of the deadliest disease on the planet. It isn't just an ailment yet additionally a maker of various types of maladies like heart assault, blurred vision, nephropathy and dyspnea. When decision-making process by traditional machine learning methods for a patient is made, it often face the following challenges: (1) some uncertain factors exist in the patient or the decision-making process which often result in misdiagnosis; (2) the decision-making process with traditional machine learning methods are block-box which are not interpretable. In this paper, a parallel-based fuzzy partition and fuzzy weighted ensemble TSK (Takagi-Sugeno-Kang) fuzzy classifier called FP-TSK-FW is proposed for diabetes diagnosis by utilizing its strong uncertainty-handling capability and interpretability so as to achieve promising classification performance. In FP-TSK-FW, the training dataset firstly is partitioned into several subsets by fuzzy clustering algorithm FCM on certain attributes, each interpretable TSK fuzzy subclassifier on each training subset can be quickly built in parallel, and with different structures. Finally, the final prediction of FP-TSK-FW is realized by fuzzy weighted for the results of each classifier. The experimental results on Pima Indians Diabetes dataset indicate the effectiveness of the proposed methods in the sense of both enhanced classification performance and interpretability.

Publisher

American Scientific Publishers

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3