CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS
نویسندگان
چکیده
منابع مشابه
Clustering Based Feature Learning on Variable Stars
The success of automatic classification of variable stars strongly depends on the lightcurve representation. Usually, lightcurves are represented as a vector of many statistical descriptors designed by astronomers called features. These descriptors commonly demand significant computational power to calculate, require substantial research effort to develop and do not guarantee good performance o...
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Feature-weight assignment can be regarded as a generalization of feature selection. That is, if all values of featureweights are either 1 or 0, feature-weight assignment degenerates to the special case of feature selection. Generally speaking, a number in 1⁄20; 1 can be assigned to a feature for indicating the importance of the feature. This paper shows that an appropriate assignment of feature...
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The linear adiabatic pulsation-periods of Mira variable stars have been derived. Approximately 2701[1]models were calculated for M = 0.7 MΘ to 2 MΘ stars with radii from 180 RΘ to 340 RΘ and luminosities from 2800 LΘ to 10,000 LΘ. The chemical composition of all models is (X,Z) = (0.7,0.02). From the result of this study, linear relations on Luminosity-Period-Mass relationship and luminosity-pe...
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ژورنال
عنوان ژورنال: The Astrophysical Journal
سال: 2016
ISSN: 1538-4357
DOI: 10.3847/0004-637x/820/2/138