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Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maxi...

Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maxi...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1709730615

Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maximum Likelihood

About this item

Full title

Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maximum Likelihood

Publisher

Cambridge, UK: Cambridge University Press

Journal title

Proceedings of the International Astronomical Union, 2014-05, Vol.10 (S306), p.319-321

Language

English

Formats

Publication information

Publisher

Cambridge, UK: Cambridge University Press

More information

Scope and Contents

Contents

We describe an approach to automate the classification of Cepheid variable stars into two subtypes according to their pulsation mode. Automating such classification is relevant to obtain a precise determination of distances to nearby galaxies, which in addition helps reduce the uncertainty in the current expansion of the universe. One main difficul...

Alternative Titles

Full title

Adapting Predictive Models for Cepheid Variable Star Classification Using Linear Regression and Maximum Likelihood

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_1709730615

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1709730615

Other Identifiers

ISSN

1743-9213

E-ISSN

1743-9221

DOI

10.1017/S1743921314013775

How to access this item