Optimization of fuzzy association rule based prediction system by genetic strategies
Feng Wang · Journal of Mechanical & Electrical Engineering · 2010
Aiming at improving the accuracy of prediction system,an optimized method which based on fuzzy association rules was proposed for prediction system designing.The method was constructed by two phase,competitive agglomeration algorithm was employed to partition quantitative attributes from each data record into several optimized fuzzy sets,resulting in an initial prediction system.And a genetic algorithm was employed to optimize rule base,which can achieve a trade-off between accuracy and interpretability.This approach was applied to the Abalone data set,and demonstrated that this method solved the redundancy in fuzzy association rules and effectively improved the prediction accuracy.