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An Expandable Light Curve Dataset for Automatic Classification of Variable Stars(LEAVES) with Its Models and Codes
Ya Fei ; Ce Yu
Based on the open datasets of ASAS-SN, Gaia and ZTF, we construct a compatible light curve dataset named LEAVES for automated recognition of variable stars, which can be used for training and testing new classification algorithms. The dataset contains a total of 977,953 variable and 134,592 non-variable light curves, in which the supported variables are divided into 6 superclasses and 9 subclasses. We validate the compatibility of the data set through experiments and employ it to train a hierarchical random forest classifier. Experimental results prove that the classifier is more compatible than the classifier established based on a single band and a single survey, and has wider applicability while ensuring classification accuracy. Here we provide the light curves of these objects by class in csv files.
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Paper Information
Paper Title:
LEAVES: An Expandable Light Curve Dataset for Automatic Classification of Variable Stars
Publication:
ApJS
Identifiers
CSTR:
11379.11.101406
DOI:
10.12149/101406
VO Identifier:
ivo://China-VO/paperdata/101406
Publication Date:
2024-09-10
Citation Guidelines
Ya Fei et al. 2024. An Expandable Light Curve Dataset for Automatic Classification of Variable Stars(LEAVES) with Its Models and Codes. Version 1.0. https://doi.org/10.12149/101406
@misc{10.12149/101406,
doi = {10.12149/101406},
url = {https://doi.org/10.12149/101406},
author = {Ya Fei},
title = {An Expandable Light Curve Dataset for Automatic Classification of Variable Stars(LEAVES) with Its Models and Codes},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2024}
}
doi = {10.12149/101406},
url = {https://doi.org/10.12149/101406},
author = {Ya Fei},
title = {An Expandable Light Curve Dataset for Automatic Classification of Variable Stars(LEAVES) with Its Models and Codes},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2024}
}
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This DOI represents all versions, and will always resolve to the latest one.
2024-09-10