An Experimental Study on the Interpretability of Fuzzy Systems

作者: José Maria Alonso , Luis Magdalena

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摘要: Interpretability is one of the most significant proper- ties Fuzzy Systems which are widely acknowledged as gray boxes against other Soft Computing techniques such Neural Networks usually regarded black boxes. It essential for applications with high human interaction (decision support systems in medicine, eco- nomics, etc). The use accuracy indices to guide fuzzy modeling process broadly extended. In turn, although there have been a few attempts define indices, we still far away from having universal index. With aim evaluating used an experimental analysis (in form web poll) was carried out yielding some useful clues keep mind regard- ing assessment. Results extracted poll show inherent subjectivity measure because collected huge diversity answers. Nevertheless, comparing carefully all an- swers, it possible find interesting user profiles. Keywords— modeling,

参考文章(20)
Paulo A. P. Fazendeiro, José Valente de Oliveira, A Working Hypothesis on the Semantics/Accuracy Synergy european society for fuzzy logic and technology conference. pp. 266- 271 ,(2005)
José M Alonso, Luis Magdalena, Serge Guillaume, None, HILK: A new methodology for designing highly interpretable linguistic knowledge bases using the fuzzy logic formalism International Journal of Intelligent Systems. ,vol. 23, pp. 761- 794 ,(2008) , 10.1002/INT.V23:7
Stephen C. Johnson, Hierarchical clustering schemes Psychometrika. ,vol. 32, pp. 241- 254 ,(1967) , 10.1007/BF02289588
Joe H. Ward, Hierarchical Grouping to Optimize an Objective Function Journal of the American Statistical Association. ,vol. 58, pp. 236- 244 ,(1963) , 10.1080/01621459.1963.10500845
Corrado Mencar, Giovanna Castellano, Anna M. Fanelli, Distinguishability quantification of fuzzy sets Information Sciences. ,vol. 177, pp. 130- 149 ,(2007) , 10.1016/J.INS.2006.04.008
Hisao Ishibuchi, Yusuke Nojima, Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning International Journal of Approximate Reasoning. ,vol. 44, pp. 4- 31 ,(2007) , 10.1016/J.IJAR.2006.01.004
L.-X. Wang, J.M. Mendel, Generating fuzzy rules by learning from examples systems man and cybernetics. ,vol. 22, pp. 1414- 1427 ,(1992) , 10.1109/21.199466
Alessio Botta, Beatrice Lazzerini, Francesco Marcelloni, Dan C. Stefanescu, Context adaptation of fuzzy systems through a multi-objective evolutionary approach based on a novel interpretability index soft computing. ,vol. 13, pp. 437- 449 ,(2008) , 10.1007/S00500-008-0360-6