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

被引:10
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
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
收藏
页码:273 / 289
页数:17
相关论文
共 89 条
[1]  
Agrawal R., 1993, SIGMOD Record, V22, P207, DOI 10.1145/170036.170072
[2]  
[Anonymous], INTELLIGENT DECISION
[3]  
[Anonymous], 2011, Pei. data mining concepts and techniques, DOI 10.1016/C2009-0-61819-5
[4]   Rough set based incremental clustering of interval data [J].
Asharaf, S ;
Murty, MN ;
Shevade, SK .
PATTERN RECOGNITION LETTERS, 2006, 27 (06) :515-519
[5]   Integrating sustainability into supplier selection with grey system and rough set methodologies [J].
Bai, Chunguang ;
Sarkis, Joseph .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2010, 124 (01) :252-264
[6]  
Bazan J.G., 2000, ROUGH SET METHODS AP, P49
[7]   Variable precision rough set theory and data discretisation: an application to corporate failure prediction [J].
Beynon, MJ ;
Peel, MJ .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2001, 29 (06) :561-576
[8]   EARLY BREAST-CANCER - PREDICTORS OF BREAST RECURRENCE FOR PATIENTS TREATED WITH CONSERVATIVE SURGERY AND RADIATION-THERAPY [J].
BOYAGES, J ;
RECHT, A ;
CONNOLLY, JL ;
SCHNITT, SJ ;
GELMAN, R ;
KOOY, H ;
LOVE, S ;
OSTEEN, RT ;
CADY, B ;
SILVER, B ;
HARRIS, JR .
RADIOTHERAPY AND ONCOLOGY, 1990, 19 (01) :29-41
[9]  
Chai J., 2013, EXPERT SYST APPL
[10]   Data mining: An overview from a database perspective [J].
Chen, MS ;
Han, JW ;
Yu, PS .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 1996, 8 (06) :866-883