计算机科学 ›› 2011, Vol. 38 ›› Issue (8): 245-247.
• 人工智能 • 上一篇 下一篇
冯林，原永乐
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FENG Lin，YUAN Yong-le
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摘要： 特征选择是模式识别和数据挖掘等研究领域的一个热点。提出了一种新的特征选择方法FeBES ( Feature Selection Based on (m+λ)-ES Evolutionary Strategy)，它以遗传算法为基础，以定义的最优特征集的评价准则为适应度函数，采用(m+λ)-ES进化策略挑选出一组较高质量的特征子集。仿真实验结果表明了该方法的有效性。
关键词: 粗糙集，特征选择，遗传算法，支持向量机
Abstract: Feature selection is one of the hot spots in the field of pattern recognition and data mining etc. A novel feature selection method, termed FeBES(Fcature Selection Based on (m+λ)-ES Evolutionary Strategy)，was proposed.Under the rule of optimization evaluation of features subset and (m+λ)-ES evolutionary strategy, a subset of features based on genetic algorithm was selected. Experimental results illustrate that the FeBES is effective for feature selection.
Key words: Rough sets, Feature selection, Uenetic algorithm, SVM
冯林，原永乐. 一种基于(m+λ)-ES进化策略的特征选择方法[J]. 计算机科学, 2011, 38(8): 245-247. https://doi.org/
FENG Lin，YUAN Yong-le. Approach for Feature Selection Based on (m+λ)-ES Evolutionary Strategy[J]. Computer Science, 2011, 38(8): 245-247. https://doi.org/
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