A New Method of Evaluation and Optimization for Feature Extraction

摘要：

The feature extraction and selection is one of the core issues of pattern recognition. In this paper, taking the feature extraction and selection for the letters A-Z and Arabic numbers 0-9 as object of study, the feature extraction methods are evaluated by calculating the sum, the variance and the minimum distance of Euclidean distance while the feature dimensions are 32, 64, 96 and 128. The arrangement of feature column element data is optimized according by their variances, the separability measure values of 1-128 dimensional features are calculated, and the Mix combination feature optimization method of feature selection for each dimension is proposed.

关键词： pattern recognition feature extraction the sum of Euclidean distance the variance of Euclidean distance evaluation and optimization

作者: Gao Jingyang Zhu Qunxiong Chen Chenglizhao

作者单位: College of Information Science & Technology, Beijing University of Chemical Technology Beijing 100029. P. R. China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Information Application(2010年计算机与信息应用国际会议 ICCIA 2010)

会议地点: 天津

会议语种:英文

页码: 40-43

在线出版日期: 2010-12-03（万方平台首次上网日期，不代表论文的发表时间）