TY - GEN
T1 - Rough set based feature selection for improved differentiation of traditional Chinese medical data
AU - Chu, Na
AU - Ma, Lizhuang
AU - Li, Jing
AU - Liu, Ping
AU - Zhou, Yang
PY - 2010
Y1 - 2010
N2 - Medical data often contains a large number of irrelevant and redundant features and a relatively small number of cases, which dramatically impact quality of diseases diagnosis. Hence, in quest for higher differentiation quality, feature selection is expected to improve differentiation performance. In this paper, we describe a heuristic approach based on Rough Sets theory and information theory, for generation of a reduct approximation of a medical dataset. The algorithm consists of two phases: initializing starting point phase and heuristic search phase. The experimental results on the medical datasets of UCI machine learning repository and traditional Chinese medicine datasets show that the proposed algorithm can efficiently select critical features and improve the performance of differentiation.
AB - Medical data often contains a large number of irrelevant and redundant features and a relatively small number of cases, which dramatically impact quality of diseases diagnosis. Hence, in quest for higher differentiation quality, feature selection is expected to improve differentiation performance. In this paper, we describe a heuristic approach based on Rough Sets theory and information theory, for generation of a reduct approximation of a medical dataset. The algorithm consists of two phases: initializing starting point phase and heuristic search phase. The experimental results on the medical datasets of UCI machine learning repository and traditional Chinese medicine datasets show that the proposed algorithm can efficiently select critical features and improve the performance of differentiation.
KW - Dimensionality reduction
KW - Liver cirrhosist
KW - Rough set
KW - Traditional Chinese medicine
UR - https://www.scopus.com/pages/publications/78649305416
U2 - 10.1109/FSKD.2010.5569782
DO - 10.1109/FSKD.2010.5569782
M3 - 会议稿件
AN - SCOPUS:78649305416
SN - 9781424459346
T3 - Proceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
SP - 2667
EP - 2672
BT - Proceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
T2 - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
Y2 - 10 August 2010 through 12 August 2010
ER -