Semi-supervised classification based on random subspace dimensionality reduction

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

95 Scopus Citations
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Author(s)

  • Guoxian Yu
  • Guoji Zhang
  • Carlotta Domeniconi
  • Zhiwen Yu
  • Jane You

Detail(s)

Original languageEnglish
Pages (from-to)1119-1135
Journal / PublicationPattern Recognition
Volume45
Issue number3
Online published30 Aug 2011
Publication statusPublished - Mar 2012
Externally publishedYes

Abstract

Graph structure is vital to graph based semi-supervised learning. However, the problem of constructing a graph that reflects the underlying data distribution has been seldom investigated in semi-supervised learning, especially for high dimensional data. In this paper, we focus on graph construction for semi-supervised learning and propose a novel method called Semi-Supervised Classification based on Random Subspace Dimensionality Reduction, SSC-RSDR in short. Different from traditional methods that perform graph-based dimensionality reduction and classification in the original space, SSC-RSDR performs these tasks in subspaces. More specifically, SSC-RSDR generates several random subspaces of the original space and applies graph-based semi-supervised dimensionality reduction in these random subspaces. It then constructs graphs in these processed random subspaces and trains semi-supervised classifiers on the graphs. Finally, it combines the resulting base classifiers into an ensemble classifier. Experimental results on face recognition tasks demonstrate that SSC-RSDR not only has superior recognition performance with respect to competitive methods, but also is robust against a wide range of values of input parameters.

Research Area(s)

  • Graph construction, Semi-supervised classification, Random subspaces, Dimensionality reduction, Ensembles of classifiers, FACE RECOGNITION, FRAMEWORK

Citation Format(s)

Semi-supervised classification based on random subspace dimensionality reduction. / Yu, Guoxian; Zhang, Guoji; Domeniconi, Carlotta et al.
In: Pattern Recognition, Vol. 45, No. 3, 03.2012, p. 1119-1135.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review