Kepler变星的监督包围分类
Supervised Ensemble Classification of Kepler Variable Stars
摘要：
变星的分析和分类是理解恒星特征和过程的一项重要任务。虽然历史上的分类是由高技能的专家手动完成的，但最近数据数量和质量的快速增长需要新技术，最值得注意的是通过监督机器学习进行自动分类。我们提出了一个扩展现有的工作领域的分析变星在{ \em开普勒}领域使用合奏的方法，结合多种表征和分类技术，以提高分类率。{ \em Kepler}观测到的大约15万颗恒星的每一颗都被分类为14个变星类。
英文摘要：
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in the quantity and quality of data has demanded new techniques, most notably automatic classification through supervised machine learning. We present an expansion of existing work on the field by analyzing variable stars in the {\em Kepler} field using an ensemble approach, combining multiple characterization and classification techniques to produce improved classification rates. Classifications for each of the roughly 150,000 stars observed by {\em Kepler} are produced separating the stars into one of 14 variable star classes.
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