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Accuracy Improvement for Diabetes Disease Classification: A Case on a Public Medical Dataset

Accuracy Improvement for Diabetes Disease Classification: A Case on a Public Medical Dataset This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). http://dx.doi.org/10.1016/j.fiae.2017.09.006 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuzzy Information and Engineering Taylor & Francis

Accuracy Improvement for Diabetes Disease Classification: A Case on a Public Medical Dataset

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References (54)

Publisher
Taylor & Francis
Copyright
© 2017 Fuzzy Information and Engineering Branch of the Operations Research Society of China. Production and hosting by Elsevier B.V. All rights reserved.
ISSN
1616-8666
eISSN
1616-8658
DOI
10.1016/j.fiae.2017.09.006
Publisher site
See Article on Publisher Site

Abstract

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). http://dx.doi.org/10.1016/j.fiae.2017.09.006

Journal

Fuzzy Information and EngineeringTaylor & Francis

Published: Sep 1, 2017

Keywords: Diabetes disease disnosis; Clustering; PCA; Neural Network

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