基于FIRST和2MASS数据库的点源分类决策表
Decision table for classifying point sources based on FIRST and 2MASS databases
摘要：
随着多波长、多尺度和多历元天文星表的出现，描述天体的特征数量有所增加。我们选择越好的特征来分类对象，分类精度就越高。本文使用了近红外波段和射电波段的恒星和类星体数据集。然后采用最佳优先搜索法进行特征选择。对于具有选定特征的数据，实现了决策表算法。分类准确率大于95.9%。因此，特征选择方法提高了分类方法的有效性和效率。结果表明，该决策表对天体的识别是鲁棒的、有效的，可用于大型巡天项目的候选类星体预选。
英文摘要：
With the availability of multiwavelength, multiscale and multiepoch astronomical catalogues, the number of features to describe astronomical objects has increases. The better features we select to classify objects, the higher the classification accuracy is. In this paper, we have used data sets of stars and quasars from near infrared band and radio band. Then best-first search method was applied to select features. For the data with selected features, the algorithm of decision table was implemented. The classification accuracy is more than 95.9%. As a result, the feature selection method improves the effectiveness and efficiency of the classification method. Moreover the result shows that decision table is robust and effective for discrimination of celestial objects and used for preselecting quasar candidates for large survey projects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
