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An Improved Fuzzy Genetics-Based Machine Learning Algorithm for Pattern Classification

An Improved Fuzzy Genetics-Based Machine Learning Algorithm for Pattern Classification,10.1109/ICICIC.2007.150,Chen-Sen Ouyang,Cheng-Tsung Lee,Shie-Ju

An Improved Fuzzy Genetics-Based Machine Learning Algorithm for Pattern Classification  
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This paper presents an improved version of the hybrid fuzzy genetics-based machine learning algorithm [3] for pattern classification. We extend the original fuzzy rule form with a single consequent class to the form with multiple consequent classes for the reason of being more general in most cases. The original fuzzy reasoning with a single winner rule is also replaced with a weighted vote method accordingly. Besides, we cancel the step of rule optimization by the Michigan-style algorithm and add a heuristic procedure to speed up the algorithm. Experimental results show that our method produces better classification results and converges more quickly than the original version.
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