1. H. Ishibuchi and T. Yamamoto. Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. Fuzzy Sets and Systems, 141(1):59-88, 2004. Keyword(s): data mining, pattern classification, fuzzy rule selection, evolutionary multi-criterion optimization, hybrid genetic algorithms. [bibtex-entry]



2. H. Ishibuchi, T. Nakashima, and T. Murata. Three-objective genetics-based machine learning for linguistic rule extraction. Information Sciences: An International Journal, 136:109-133, 2001. Keyword(s): pattern classification, fuzzy systems, genetic algorithm, rule extraction. [bibtex-entry]



3. H. Ishibuchi and M. Nii. Neural networks for soft decision making. Fuzzy Sets and Systems, 115:121-140, 2000. Keyword(s): neural networks, soft decision, reject option, interval arithmetic, fuzzy arithmetic. [bibtex-entry]



4. H. Ishibuchi, T. Nakashima, and T. Morisawa. Voting in fuzzy rule-based systems for pattern classification problems. Fuzzy Sets and Systems, 103:223-238, 1999. Keyword(s): pattern classification, fuzzy rule-based systems, fuzzy reasoning, voting schemes. [bibtex-entry]



5. H. Ishibuchi, T. Murata, and M. Gen. Performance evaluation of fuzzy rule-based classification systems obtained by multi- objective genetic algorithms. Computers & Industrial Engineering, 35(3-4):575-578, 1998. Keyword(s): fuzzy rule-based system, pattern classification, rule selection, genetic algorithm, knowledge acquisition. [bibtex-entry]



6. H. Ishibuchi, T. Murata, and I. Türksen. Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems. Fuzzy Sets and Systems, 89(2):135-150, 1997. Keyword(s): linguistic modeling, pattern recognition, data analysis, genetic algorithm, rule selection. [bibtex-entry]

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