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应用 AutoClass 算法聚类分析 SDSS 巡天的恒星数据 PowerPoint PPT Presentation


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应用 AutoClass 算法聚类分析 SDSS 巡天的恒星数据. 严太生. 2008 年 11 月于太原. 提纲. 恒星自动分类 / 聚类的背景 AutoClass 算法 SDSS 数字巡天及参数选取 AutoClass 分类结果及讨论 结论. 1 恒星自动分类 / 聚类的背景. 一个完整详细的恒星样本不仅对于恒星的基本组成 , 演化历史 , 而且对于研究星系结构和演化都有很重要的意义。 随着从地面和空间观测设备获取大量的数据 , 构建大的完整的样本成为可能。 为了提高分类 / 聚类的效率,我们需要依靠区别性很好的分类器。.

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应用 AutoClass 算法聚类分析 SDSS 巡天的恒星数据

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AutoClassSDSS

200811


  • /

  • AutoClass

  • SDSS

  • AutoClass


1 /

  • ,,

  • ,

  • /


/

  • ABazarghan (2008) OM5000158

  • BGLIMPSEMercer (2005)

  • CWozniak (2004) 8678

  • DFroebrich (2008) -/

  • EJaschek (1990) ,


2 AutoClass

  • AutoClassBayesian AutoClassBernoulli


AutoClass

  • A

  • B

  • C

  • D

  • E

    AutoClass


3 SDSS

  • ASDSS

    SDSS267591851/49312


B

SDSS DR6140865

5psf_u-u,psf_g-g,psf_r-r,psf_i-I,psf_z-z)PSF


4 AutoClass

  • AAutoClass

    starsnon-starsnon-starsAutoClassSingle_normalsearch139874stars991non-stars


Non-stars

StarsNon-stars

  • i-

Stars


Non-stars

  • ii-

Stars


  • B non-stars

    AutoClassnon-starsnon-stars


iSIMBAD


SIMBADnon-stars225non-stars25non-stars/-


iiNED


NEDnon-stars650non-stars50non-stars/-


iiiSDSS image/spectra


SIMBADNEDnon-stars,

10non-stars10


Cnon-starsSIMBAD NEDSDSS image/spectra76.0%98.0%80.0%89.4%


D

i

iistarsnon-stars

iii AutoClass


i--starsnon-stars non-stars2non-starsAutoClass

iiSIMBADNED- non-stars-

iiiNEDnon-stars



5

AutoClass SDSS


inon-starsgalaxy,HII,late-star

iiAutoClass

iiinon-stars

iv90%AutoClass

vnon-stars

vinon-stars


non-stars



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