Artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. Construction of optimized weighted fuzzy decision tree is an NP-Hard problem. In this paper, we propose two optimization methods to increase the classification efficiency of weighted fuzzy decision tree algorithm. In this work ABC algorithm is used for optimizing weighted fuzzy decision tree. In order to evaluate the performance of the proposed techniques, we applied it to three benchmark datasets. The results indicate that the proposed approachs have a higher accuracy than Fuzzy ID3, weighted FDT and OWFDT methods.
کلید واژگان :Artificial Bee Colony (ABC) algorithm, Fuzzy ID3, weighted fuzzy decision tree, feature selection, optimization
ارزش ریالی : 600000 ریال
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