Stellar Spectra Classification with Entropy-Based Learning Machine

doi:10.3964/j.issn.1000-0593(2018)02-0660-05

	Stellar Spectra Classification with Entropy-Based Learning Machine
	Liu Zhong-bao 2; Fu Li-zhen 2; Ren Juan-juan 1; Song Wen-ai 2; Kong Xiao1 ; Zhang Jing2
刊名	SPECTROSCOPY AND SPECTRAL ANALYSIS
	2018-02-01
卷号	38 期号:2 页码:660-664
关键词	Data Mining Stellar Spectra Classification Entropy Sloan Digital Sky Survey (Sdss)
DOI	10.3964/j.issn.1000-0593(2018)02-0660-05
文献子类	Article
英文摘要	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.
WOS研究方向	Spectroscopy
语种	英语
WOS记录号	WOS:000426142100054
资助机构	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
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/20302]
专题	国家天文台_光学天文研究部
作者单位	1.Chinese Acad Sci, Key Lab Opt Astron, Natl Astron Observ, Beijing 100012, Peoples R China 2.North Univ China, Sch Software, Taiyuan 030051, Shanxi, Peoples R China
推荐引用方式 GB/T 7714	Liu Zhong-bao,Fu Li-zhen,Ren Juan-juan,et al. Stellar Spectra Classification with Entropy-Based Learning Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2018,38(2):660-664.
APA	Liu Zhong-bao,Fu Li-zhen,Ren Juan-juan,Song Wen-ai,Kong Xiao,&Zhang Jing.(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.