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An improvement on learning with local and global consistency

  • CAS - Institute of Intelligent Machines
  • University of Science and Technology of China

科研成果: 书/报告/会议事项章节会议稿件同行评审

11 引用 (Scopus)

摘要

A modified version for semi-supervised learning algorithm with local and global consistency was proposed in this paper. The new method adds the label information, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting calculation. In addition we add class prior knowledge. It was found that the effect of class prior knowledge was different between under high label rate and low label rate. The experimental results show that the changes attain the satisfying classification performance better than the original algorithms.

源语言英语
主期刊名2008 19th International Conference on Pattern Recognition, ICPR 2008
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(印刷版)9781424421756
DOI
出版状态已出版 - 2008
已对外发布

出版系列

姓名Proceedings - International Conference on Pattern Recognition
ISSN(印刷版)1051-4651

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