Attribute reduction based on background knowledge and its application in classification of astronomical spectra data |
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| Authors: | Zhang Jifu Li Yinhua Zhang Sulan |
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| Institution: | 1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, P.R.China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P.R.China
2. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, P.R.China |
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| Abstract: | To improve the efficiency of the attribute reduction,we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields.Under the condition of known background knowledge,the algorithm Can not only greatly improve the efficiency of attribute reduction,but also avoid the defection of information entropy partial to attribute with much value.The experimental result verifies that the algorithm is effective.In the end,the algorithm produces better results when applied in the classification of the star spectra data. |
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| Keywords: | rough set theory background knowledge information entropy attribute reduction astronomical spectra data |
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