Rough set based rule induction in decision making using credible classification and preference from medical application perspective

被引：12

作者：

Tseng, Tzu-Liang ^{[1
]}

Huang, Chun-Che ^{[2
]}

Fraser, Kym ^{[3
]}

Ting, Hsien-Wei ^{[4
]}

机构：

[1] Univ Texas El Paso, Dept Ind Mfg & Syst Engn, 500 West Univ Ave, El Paso, TX 79968 USA

[2] Natl Chi Nan Univ, Dept Informat Management, 1 Univ Rd, Puli 545, Taiwan

[3] Univ S Australia, Barbara Hardy Inst, Adelaide, SA 5001, Australia

[4] Yuan Ze Univ, Dept Neurosurg, Taipei Hosp, Dept Informat Management, 127 Su Yuan Rd, New Taipei, Taiwan

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2016年 / 127卷

关键词：

Rough set theory; Credible index; Rule induction; Medical prediction; PATTERN DISCOVERY; FAULT-DIAGNOSIS; FUZZY-SETS; KNOWLEDGE; SYSTEM; CANCER;

D O I：

10.1016/j.cmpb.2015.12.015

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a new heuristic algorithm for reduct selection based on credible index in the rough set theory (RST) applications. This algorithm is efficient and effective in selecting the decision rules particularly the problem to be solved in a large scale. This algorithm is capable to derive the rules with multi-outcomes and identify the most significant features simultaneously, which is unique and useful in solving predictive medical problems. The end results of the proposed approach are a set of decision rules that illustrates the causes for solitary pulmonary nodule and results of the long term treatment. (C) 2015 Elsevier Ireland Ltd. All rights reserved.

引用

页码：273 / 289

页数：17

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