Semi-supervised ensemble clustering based on selected constraint projection

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

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Author(s)

  • Zhiwen Yu
  • Peinan Luo
  • Jiming Liu
  • Jane You
  • Guoqiang Han
  • Jun Zhang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)2394-2407
Journal / PublicationIEEE Transactions on Knowledge and Data Engineering
Volume30
Issue number12
Early online date23 Mar 2018
StatePublished - 1 Dec 2018

Abstract

Traditional cluster ensemble approaches have several limitations. (1) Few make use of prior knowledge provided by experts. (2) It is difficult to achieve good performance in high-dimensional datasets. (3) All of the weight values of the ensemble members are equal, which ignores different contributions from different ensemble members. (4) Not all pairwise constraints contribute to the final result. In the face of this situation, we propose double weighting semi-supervised ensemble clustering based on selected constraint projection(DCECP) to address these limitations. Specifically, DCECP first adopts the random subspace technique in combination with the constraint projection procedure to handle high-dimensional datasets. Second, it treats prior knowledge of experts as pairwise constraints, and assigns different subsets of pairwise constraints to different ensemble members. An adaptive ensemble member weighting process is designed to associate different weight values with different ensemble members. Third, the weighted normalized cut algorithm is adopted to summarize clustering solutions and generate the final result. Finally, nonparametric statistical tests are used to compare multiple algorithms on real-world datasets. Our experiments on 15 high-dimensional datasets show that DCECP performs better than most clustering algorithms.

Research Area(s)

  • Cluster ensemble, Clustering algorithms, Computer science, Data mining, Electronic mail, Face, Gene expression, Indexes, pairwise constraint, projection, semi-supervised clustering

Citation Format(s)

Semi-supervised ensemble clustering based on selected constraint projection. / Yu, Zhiwen; Luo, Peinan; Liu, Jiming; Wong, Hau-San; You, Jane; Han, Guoqiang; Zhang, Jun.

In: IEEE Transactions on Knowledge and Data Engineering, Vol. 30, No. 12, 01.12.2018, p. 2394-2407.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review