Singular vector decomposition based hybrid pattern search - An efficient co-clustering method

Debby D. Wang, Haoran Xie, Fu Lee Wang, Hong Yan

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)

Abstract

With the rapid development of machine-learning and data-mining techniques, biclustering (co-clustering) has become an important and widespread technique in multiple areas such as gene expression analysis, text mining and market segmentation. In this work, we proposed an efficient co-clustering method named SVD-based hybrid pattern search (SHPS). It is a score-function-based method, and specifically both the mean-square-residue and correlation-based scores were tested in our studies. For a data matrix, SHPS first uses SVD layers to approximate it, and then searches the SVD subspaces for hybrid patterns (cliquish or linear) along the row or column direction. Groups along the two directions are combined, and those with a score smaller than a pre-defined threshold will be outputted. After testing our method on multiple types of matrices and comparing it with the traditional Cheng and Church method, SHPS showed a good performance with multiple co-clusters and better scores. Additionally, using more SVD layers may further improve the results. Overall, SHPS can be a good and efficient alternative in future co-clustering-related studies and applications.

Original languageEnglish
Title of host publicationProceedings of 2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016
PublisherIEEE Computer Society
Pages269-274
Number of pages6
ISBN (Electronic)9781509003891
DOIs
Publication statusPublished - 2 Jul 2016
Externally publishedYes
Event2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016 - Jeju Island, Korea, Republic of
Duration: 10 Jul 201613 Jul 2016

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume1
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016
CountryKorea, Republic of
CityJeju Island
Period10/07/1613/07/16

Keywords

  • Co-clustering
  • Pattern search
  • Singular vector decomposition (SVD)
  • SVD layer

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    Wang, D. D., Xie, H., Wang, F. L., & Yan, H. (2016). Singular vector decomposition based hybrid pattern search - An efficient co-clustering method. In Proceedings of 2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016 (pp. 269-274). [7860912] (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICMLC.2016.7860912