Automatic Classification Method of Star Spectra Data Based on Manifold Fuzzy Twin Support Vector Machine
LIU Zhong-bao1, GAO Yan-yun2, WANG Jian-zhen3
1. School of Electronics and Computer Science Technology, North University of China, Taiyuan 030051, China 2. Human Resource Department, Henan Information and Statistics Vocational College, Zhengzhou 450008, China 3. School of Information, Business College of Shanxi University, Taiyuan 030031, China
摘要： 支持向量机(support vector machine, SVM)具有良好的学习性能和泛化能力，因而被广泛应用于恒星光谱分类中。然而实际应用面临的数据规模往往很大，SVM便暴露出计算量大、分类速度慢等问题。为了解决上述问题，Jayadeva等提出双支持向量机(twin support vector machine, TWSVM)，将计算时间减少至SVM的1/4。然后上述方法仅关注数据的全局特征，对每类数据的局部特征并未关注。鉴于此，提出基于流形模糊双支持向量机(manifold fuzzy twin support vector machine, MF-TSVM)的恒星光谱分类方法。利用流形判别分析获得数据的全局特征和局部特征，模糊隶属度函数的引入将各类数据区别对待，尽可能减少噪声点和奇异点对分类结果的影响。与C-SVM，KNN等传统分类方法在SDSS恒星光谱数据集上的比较实验表明了该方法的有效性。
关键词：自动分类;恒星光谱;流形判别分析;模糊隶属度;双支持向量机
Abstract：Support vector machine (SVM) with good leaning ability and generalization is widely used in the star spectra data classification. But when the scale of data becomes larger, the shortages of SVM appear: the calculation amount is quite large and the classification speed is too slow. In order to solve the above problems, twin support vector machine (TWSVM) was proposed by Jayadeva. The advantage of TSVM is that the time cost is reduced to 1/4 of that of SVM. While all the methods mentioned above only focus on the global characteristics and neglect the local characteristics. In view of this, an automatic classification method of star spectra data based on manifold fuzzy twin support vector machine (MF-TSVM) is proposed in this paper. In MF-TSVM, manifold-based discriminant analysis (MDA) is used to obtain the global and local characteristics of the input data and the fuzzy membership is introduced to reduce the influences of noise and singular data on the classification results. Comparative experiments with current classification methods, such as C-SVM and KNN, on the SDSS star spectra datasets verify the effectiveness of the proposed method.
刘忠宝1，高艳云2，王建珍3 . 基于流形模糊双支持向量机的恒星光谱分类方法 [J]. 光谱学与光谱分析, 2015, 35(01): 263-266.
LIU Zhong-bao1, GAO Yan-yun2, WANG Jian-zhen3 . Automatic Classification Method of Star Spectra Data Based on Manifold Fuzzy Twin Support Vector Machine . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(01): 263-266.
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