计算机工程2012，Vol.38Issue(8)：173-176,4.DOI:10.3969/j.issn.1000-3428.2012.08.057
迁移学习数据分类中的ESVM算法
ESVM Algorithm in Transfer Learning Data Classification
张建军 1王士同 1王骏2
作者信息
- 1. 江南大学信息工程学院,江苏无锡214122
- 2. 南京理工大学计算机科学与技术学院,南京210094
- 折叠
摘要
Abstract
In transfer learning process, noise makes the result unreasonable when you classify slow changing dataset. Here is an algorithm called Extended Support Vector Machine(ESVM) proposed to solve this problem. Because it makes full use of probability distribution of original data and uses the learning experience of the previous dataset to classify the latter dataset, ES VM can correctly classify the changing dataset with inheriting the characteristics from the previous dataset. Experimental result shows the antinoise performance of the algorithm.关键词
迁移学习/分类/支持向量机/继承经验/抗噪性能Key words
transfer learning/classification/Support vector Machine(SVM)/inheriting experience/antinoise performance分类
信息技术与安全科学引用本文复制引用
张建军,王士同,王骏..迁移学习数据分类中的ESVM算法[J].计算机工程,2012,38(8):173-176,4.
