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	Intelligent Feature Extraction and Knowledge Mining by Multivariate Analyses
	Chen, Yisong ; Cui, Hong
	2009
关键词	DATA VISUALIZATION FEATURE-SELECTION CLASSIFICATION ALGORITHMS TREES MODEL
英文摘要	A new knowledge mining framework based on multivariate analyses is proposed to discover and simulate the school grading policy. The framework comprises three major steps. Firstly, factor analysis is adopted to separate the scores of several different subjects into grading-related ones and grading-unrelated ones. Secondly, multidimensional scaling is employed for dimensionality reduction to facilitate subsequent data visualization and interpretation. Finally, a support vector machine is trained to classify the filtered data into different grades. This work provides an attractive framework for intelligent data analysis and decision-making. It also exhibits the advantages of high classification accuracy and supports intuitive data interpretation.; Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/CIDM.2009.4938626
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/406340]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Chen, Yisong,Cui, Hong. Intelligent Feature Extraction and Knowledge Mining by Multivariate Analyses. 2009-01-01.

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