NAOC Open IR
distinguishingtherarespectrawiththeunbalancedclassificationmethodbasedonmutualinformation
Liu Zhongbao1; Ren Juanjuan2; Kong Xiao3
2016
Source Publication光谱学与光谱分析
ISSN1000-0593
Volume36Issue:11Pages:3746
AbstractDistinguishing the rare spectra from the majority of stellar spectra is one of quite important issues in astronomy. As the size of the rare spectra is much smaller than the majority of the spectra, many traditional classifiers can't work effectively because they only focus on the classification accuracy and have not paid e-nough attentions on the rare spectra. In view of this,the relationship between the decision tree and mutual information is discussed on the basis of summarizing the traditional classifiers, and the cost-free decision tree based on mutual information is proposed in this paper to improve the performance of distinguishing the rare spectra. In the experiment, we investigate the performance of the proposed method on the K-type,F-type, G-type, M-type datasets from Sloan Digital Sky Survey (SDSS),Data Release 8. It can be concluded that the proposed method can complete the rare spectra distinguishing task compared with several traditional classifiers.
Language英语
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/43365
Collection中国科学院国家天文台
Affiliation1.中北大学
2.中国科学院
3.中国科学院国家天文台
Recommended Citation
GB/T 7714
Liu Zhongbao,Ren Juanjuan,Kong Xiao. distinguishingtherarespectrawiththeunbalancedclassificationmethodbasedonmutualinformation[J]. 光谱学与光谱分析,2016,36(11):3746.
APA Liu Zhongbao,Ren Juanjuan,&Kong Xiao.(2016).distinguishingtherarespectrawiththeunbalancedclassificationmethodbasedonmutualinformation.光谱学与光谱分析,36(11),3746.
MLA Liu Zhongbao,et al."distinguishingtherarespectrawiththeunbalancedclassificationmethodbasedonmutualinformation".光谱学与光谱分析 36.11(2016):3746.
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