A STUDY ON THE ERROR OF DISTRIBUTED ALGORITHMS FOR BIG DATA CLASSIFICATION WITH SVM

被引：0
|
作者：
Wang, Cheng [1 ]
Cao, Feilong [1 ]
机构：
[1] China Jiliang Univ, Appl Math Dept, Hangzhou, Zhejiang, Peoples R China
来源：
ANZIAM JOURNAL | 2017年 / 58卷 / 3-4期
基金：
中国国家自然科学基金;
关键词：
distributed algorithm; big data; support vector machine; Tsybakov exponent; geometric noise exponent;
D O I：
10.1017/S1446181116000390
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The error of a distributed algorithm for big data classification with a support vector machine (SVM) is analysed in this paper. First, the given big data sets are divided into small subsets, on which the classical SVM with Gaussian kernels is used. Then, the classification error of the SVM for each subset is analysed based on the Tsybakov exponent, geometric noise, and width of the Gaussian kernels. Finally, the whole error of the distributed algorithm is estimated in terms of the error of each subset.
引用
收藏
页码：231 / 237
页数：7
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