Constraint-Based Semi-Supervised Dimensionality Reduction with Conflict Detection

被引：0
|
作者：
Chen, Binhui [1 ]
Bai, Qingyuan [1 ]
机构：
[1] Fuzhou Univ, Sch Math & Comp Sci, Fuzhou 350002, Peoples R China
来源：
2010 3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2010), VOLS 1-7 | 2010年
关键词：
SSDR; conflict detection; semi-supervised learning; adjustment of constraints; clustering analysis;
D O I：
10.1109/BMEI.2010.5639901
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Most existing typical semi-supervised learning algorithms focused on the results of learning while facing the conflict on constraints. And most solutions use unsupervised distance-based methods to adjust the conflicting constraints on the information by recalculating the samples distance. This paper presents a constraint-based semi-supervised dimensionality reduction algorithm with conflict detection, called CDSSDR, which uses the information of priori constraints to adjust the contradictions in the constraints. It avoids the use of unsupervised methods to adjust the prior knowledge.
引用
收藏
页码：3036 / 3040
页数：5
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