Feature Selection of Combining Relieff and Rough Set for Syndrome Classification of Chronic Gastritis in Traditional Chinese Medicine

DOI

10.2991/asei-15.2015.242How to use a DOI?

Keywords

Relieff; Rough Set; Multi-Label Learning; Syndrome Classification; TCM

Abstract

Typically, the main form of Chinese medicine is based on interrogation of the patient's condition and artificial judgement by asking related patient symptom information; which is strongly subjective and prone to errors of judgment, leading to the wrong treatment outcome. The development in computer greatly improved the level of research in medicine, and also allowed the gradually objective and systematic improvement of experience knowledge. By analyzing TCM inquiry chronic gastritis data, the Relieff & Rough Set feature selection method was presented by combining different classification algorithms with experiments and analysis; the experimental results showed that efficient feature selection method can greatly enhance the effect of the classification; therefore, Relieff & Rough Set can be used as an efficient tool for feature selection and applied in the syndrome classification of TCM.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jianjun Yan
AU  - Qiyue Chen
AU  - Guoping Liu
AU  - Xiong Lu
AU  - Yiqin Wang
AU  - Rui Guo
PY  - 2015/05
DA  - 2015/05
TI  - Feature Selection of Combining Relieff and Rough Set for Syndrome Classification of Chronic Gastritis in Traditional Chinese Medicine
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 1233
EP  - 1237
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.242
DO  - 10.2991/asei-15.2015.242
ID  - Yan2015/05
ER  -