Biclustering Performance Evaluation of Cheng and Church Algorithm and Iterative Signature Algorithm

Authors

  • I Made Sumertajaya Sumertajaya Department of Statistics, IPB University http://orcid.org/0000-0002-2682-7941
  • Wiwik Andriyani Lestari Ningsih BPS-Statistics
  • Asep Saefuddin Department of Statistics, IPB University
  • Embay Rohaeti Departement of Mathematics, FMIPA, Pakuan University

DOI:

https://doi.org/10.31764/jtam.v7i3.14778

Keywords:

Biclustering, Cheng and Church algorithm, Inter bicluster, Intra bicluster, Iterative signature algorithm.

Abstract

Biclustering has been widely applied in recent years. Various algorithms have been developed to perform biclustering applied to various cases. However, only a few studies have evaluated the performance of bicluster algorithms. Therefore, this study evaluates the performance of biclustering algorithms, namely the Cheng and Church algorithm (CC algorithm) and the Iterative Signature Algorithm (ISA). Evaluation of the performance of the biclustering algorithm is carried out in the form of a comparative study of biclustering results in terms of membership, characteristics, distribution of biclustering results, and performance evaluation. The performance evaluation uses two evaluation functions: the intra-bicluster and the inter-bicluster. The results show that, from an intra-bicluster evaluation perspective, the optimal bicluster group of the CC algorithm produces bicluster quality which tends to be better than the ISA. The biclustering results between the two algorithms in inter-bicluster evaluation produce a deficient level of similarity (20-31 percent). This is indicated by the differences in the results of regional membership and the characteristics of the identifying variables. The biclustering results of the CC algorithm tend to be homogeneous and have local characteristics. Meanwhile, the results of biclustering ISA tend to be heterogeneous and have global characteristics. In addition, the results of biclustering ISA are also robust.

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Published

2023-07-17

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Vol. 7 No. 3 (2023): July

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