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Stellar Spectra Classification with Entropy-Based Learning Machine
Liu Zhong-bao1; Ren Juan-juan2; Song Wen-ai1; Zhang Jing1; Kong Xiao2; Fu Li-zhen1
2018-02-01
发表期刊SPECTROSCOPY AND SPECTRAL ANALYSIS
卷号38期号:2页码:660-664
摘要Data mining are widely used in the stellar spectra classification. In order to improve the efficiencies of traditional spectra classification methods, Entropy-based Learning Machine (ELM) was proposed in this paper. The entropy was used to describe the uncertainty of classification in ELM. In order to obtain the desired classification efficiencies, the classification uncertainty should be minimized, based on which, we can obtain the optimization problem of ELM. It can be verified that ELM performs well in the binary classification and in the rare spectra mining. Several comparative experiments on the 4 subclasses of K-type spectra, 3 subclasses of F-type spectra and 3 subclasses of G-type spectra from Sloan Digital Sky Survey (SDSS) verified that ELM performs better than kNN (k Nearest Neighbor) and SVM (Support Vector Machine) in dealing with the problem of stellar spectra classification on the SDSS datasets.
文章类型Article
关键词Data Mining Stellar Spectra Classification Entropy Sloan Digital Sky Survey (Sdss)
WOS标题词Science & Technology ; Technology
资助者Nature Science Foundation of Shanx(201601D011042) ; Nature Science Foundation of Shanx(201601D011042) ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Nature Science Foundation of Shanx(201601D011042) ; Nature Science Foundation of Shanx(201601D011042) ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China
DOI10.3964/j.issn.1000-0593(2018)02-0660-05
收录类别SCI
语种英语
资助者Nature Science Foundation of Shanx(201601D011042) ; Nature Science Foundation of Shanx(201601D011042) ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Nature Science Foundation of Shanx(201601D011042) ; Nature Science Foundation of Shanx(201601D011042) ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China ; Program for the Outstanding Innovative Team of High Learning Learning Instituttions of Shanxi, Outstanding Youth Funds of North University of China
WOS研究方向Spectroscopy
WOS类目Spectroscopy
WOS记录号WOS:000426142100054
引用统计
文献类型期刊论文
条目标识符http://ir.bao.ac.cn/handle/114a11/20302
专题光学天文研究部
作者单位1.North Univ China, Sch Software, Taiyuan 030051, Shanxi, Peoples R China
2.Chinese Acad Sci, Key Lab Opt Astron, Natl Astron Observ, Beijing 100012, Peoples R China
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Liu Zhong-bao,Ren Juan-juan,Song Wen-ai,et al. Stellar Spectra Classification with Entropy-Based Learning Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2018,38(2):660-664.
APA Liu Zhong-bao,Ren Juan-juan,Song Wen-ai,Zhang Jing,Kong Xiao,&Fu Li-zhen.(2018).Stellar Spectra Classification with Entropy-Based Learning Machine.SPECTROSCOPY AND SPECTRAL ANALYSIS,38(2),660-664.
MLA Liu Zhong-bao,et al."Stellar Spectra Classification with Entropy-Based Learning Machine".SPECTROSCOPY AND SPECTRAL ANALYSIS 38.2(2018):660-664.
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