Parameters optimization of classifier and feature selection based on improved artificial bee colony algorithm
作者： Haiquan Wang , Hongnian Yu , Qian Zhang , Shuang Cang , Wudai Liao
DOI: 10.1109/ICAMECHS.2016.7813454
关键词:
摘要: The feature subset selection, along with the parameters of classifier significantly influences classification accuracy. In order to ensure optimal performance, artificial bee colony (ABC) algorithm is proposed simultaneously optimize and support vector machines (SVM), meanwhile for improving optimizing performance ABC algorithm, initialization scout phase are improved. To evaluate approach, simulation was executed based on datasets from UCI database. effectiveness method confirmed by results.
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