Feature Extraction and Classification for Graphical Representations of Data

Authors:
Jinjia Wang;Jing Li;Wenxue Hong
Affiliations:
College of Information Science and Engineer, Yanshan University, Qinhuangdao 066004 and College of Electrical Engineering, Yanshan University, Qinhuangdao, China 066004;Colleges of Science, Yanshan University, Qinhuangdao, China 066004;College of Electrical Engineering, Yanshan University, Qinhuangdao, China 066004
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Year:
2008

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Abstract

The barycentre graphical feature extraction method of the star plot is proposed, based on the graphical representation of multi-dimensional data. Because for the different feature order the same multi-dimensional data lead to the different star plots, and extract the different barycentre graphical features, which affect the classification error of the classifiers. The novel feature order method based on the improved genetic algorithm (GA) is proposed. Meanwhile the traditional feature order method based on the feature selection is researched and the traditional vector feature extraction methods are researched. The experiments results of the 4 real data sets show the classification effectiveness of the new graphical representation and graphical features.