计算机工程与应用2016，Vol.52Issue(16)：79-84,120,7.DOI:10.3778/j.issn.1002-8331.1411-0188
基于数据分布一致性最小最大概率机
Minimax probability machine with concensus regularization between data distributions
王晓初 1王士同 1包芳2
作者信息
- 1. 江南大学 数字媒体学院，江苏 无锡 214122
- 2. 江阴职业技术学院，江苏 无锡 214405
- 折叠
摘要
Abstract
A minimax probability machine, called DCMPM, with the consensus regularization between data distributions is proposed for data classification in which the data contain labeled and unlabeled samples in this paper. In the proposed machine, labeled and unlabeled samples be mapped to the space of decision hyperplane and then the decision hyperplane is revised by minimizing the difference of the probability distributions between labeled and unlabeled samples such that the revised decision hyperplane is more close to the real classification hyperplane. Experimental results indicate the power of the proposed method.关键词
数据分布一致性/最小最大概率机/决策超平面Key words
data distributions/minimax probability machine/decision hyperplane分类
信息技术与安全科学引用本文复制引用
王晓初,王士同,包芳..基于数据分布一致性最小最大概率机[J].计算机工程与应用,2016,52(16):79-84,120,7.
