Combination of classification and clustering results with label propagation

Xu Yao Zhang, Peipei Yang, Yan Ming Zhang, Kaizhu Huang, Cheng Lin Liu

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


This letter considers the combination of multiple classification and clustering results to improve the prediction accuracy. First, an object-similarity graph is constructed from multiple clustering results. The labels predicted by the classification models are then propagated on this graph to adaptively satisfy the smoothness of the prediction over the graph. The convex learning problem is efficiently solved by the label propagation algorithm. A semi-supervised extension is also provided to further improve the performance. Experiments on 11 tasks identify the validity of the proposed models.

Original languageEnglish
Article number6767106
Pages (from-to)610-614
Number of pages5
JournalIEEE Signal Processing Letters
Issue number5
Publication statusPublished - May 2014


  • Classification
  • Clustering
  • Label propagation


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