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基于遗传算法的高维特征选择的研究 预览 被引量:1

Research on high-dimensional feature selection based on genetic algorithms
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摘要 针对手写体数字提取的特征维数过高且有冗余从而影响识别速度的问题,提出了基于遗传算法的高维特征选择方法.遗传算法采用类内类间比作为适应度函数,识别率高但速度较慢;而对手写体数字识别的仿真实验表明,特征选择方法虽然识别率在一定程度上有所下降,但提高了识别速度. Aimed to the phenomenon that the extracted feature dimension of the handwritten numeral is too high and redundant, a high-dimensional feature selection method was proposed using genetic algorithms whose fitness function is the ratio of intra-class and inter-class, which has high recognition rate but low speed. The simulation results on the handwritten digital recognition showed that although the rocognition rate of feature selection decreased to some extent, the speed of the recognition increased.
作者 吴进文 赵晓翠 陈苗苗 WU Jin-wen , ZHAO Xiao-cui , CHEN Miao-miao ( 1. College of Comp. and Infor. Eng. ,Henan Univ. of Finance & Economics ,Zhengzhou 450002, China; 2. School of Finance and Insurance, Zhongnan Univ. of Economics and Law, Wuhan 430074, China)
出处 《郑州轻工业学院学报:自然科学版》 2010年第2期 75-78,共4页 Journal of Zhengzhou University of Light Industry:Natural Science
关键词 类内类间比 特征选择 遗传算法 手写体 数字识别 the ratio of intra-class and inter-class feature selection genetic algorithm handwritten numeral digital recognition
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参考文献7

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