A hybrid model combining case-based reasoning and fuzzy decision tree for medical data classification
作者： Chin-Yuan Fan , Pei-Chann Chang , Jyun-Jie Lin , J.C. Hsieh
DOI: 10.1016/J.ASOC.2009.12.023
关键词:
摘要: In this research, a hybrid model is developed by integrating case-based data clustering method and fuzzy decision tree for medical classification. Two datasets from UCI Machine Learning Repository, i.e., liver disorders dataset Breast Cancer Wisconsin (Diagnosis), are employed benchmark test. Initially applied to preprocess the thus more homogeneous within each cluster will be attainted. A then in genetic algorithms (GAs) further construct decision-making system based on selected features diseases identified. Finally, set of rules generated cluster. As result, FDT can accurately react test inductions derived tree. The average forecasting accuracy breast cancer CBFDT 98.4% 81.6%. highest among those models compared. produce accurate but also comprehensible that could potentially help doctors extract effective conclusions diagnosis.
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C LEE, M WANG, Ontology-based intelligent healthcare agent and its application to respiratory waveform recognition Expert Systems With Applications. ,vol. 33, pp. 606- 619 ,(2007) , 10.1016/J.ESWA.2006.06.006
Kun Chang Lee, Sang Bong Oh, An intelligent approach to time series identification by a neural network-driven decision tree classifier decision support systems. ,vol. 17, pp. 183- 197 ,(1996) , 10.1016/0167-9236(95)00031-3
Ioannis Gadaras, Ludmil Mikhailov, An interpretable fuzzy rule-based classification methodology for medical diagnosis Artificial Intelligence in Medicine. ,vol. 47, pp. 25- 41 ,(2009) , 10.1016/J.ARTMED.2009.05.003
David B. Fogel, Eugene C. Wasson, Edward M. Boughton, Evolving neural networks for detecting breast cancer. Cancer Letters. ,vol. 96, pp. 49- 53 ,(1995) , 10.1016/0304-3835(95)03916-K
Edward I. Altman, Giancarlo Marco, Franco Varetto, Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) Journal of Banking and Finance. ,vol. 18, pp. 505- 529 ,(1994) , 10.1016/0378-4266(94)90007-8
Yuh-Jye Lee, O.L. Mangasarian, SSVM: A Smooth Support Vector Machine for Classification Computational Optimization and Applications. ,vol. 20, pp. 5- 22 ,(2001) , 10.1023/A:1011215321374
Carlos Andrés Peña-Reyes, Moshe Sipper, A fuzzy-genetic approach to breast cancer diagnosis. Artificial Intelligence in Medicine. ,vol. 17, pp. 131- 155 ,(1999) , 10.1016/S0933-3657(99)00019-6
Robert K. Lai, Chin-Yuan Fan, Wei-Hsiu Huang, Pei-Chann Chang, Evolving and clustering fuzzy decision tree for financial time series data forecasting Expert Systems with Applications. ,vol. 36, pp. 3761- 3773 ,(2009) , 10.1016/J.ESWA.2008.02.025
Xiao-ning Song, Yu-jie Zheng, Xiao-jun Wu, Xi-bei Yang, Jing-yu Yang, None, A complete fuzzy discriminant analysis approach for face recognition Applied Soft Computing. ,vol. 10, pp. 208- 214 ,(2010) , 10.1016/J.ASOC.2009.07.002
P CHANG, Y WANG, Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry Expert Systems With Applications. ,vol. 30, pp. 715- 726 ,(2006) , 10.1016/J.ESWA.2005.07.031