Feature selection based on closed frequent itemset mining: A case study on SAGE data classification

Author:

Seeja K.R.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference24 articles.

1. R.T. Ng, J. Sander, Μ.C. Sleumer. Hierarchical cluster analysis of SAGE data for cancer profiling, in: Proceedings of Workshop on Data Mining in Bioinformatics, 2001, pp. 65-72.

2. G. Tzanis, I. Vlahavas. Mining high quality clusters of SAGE data, in: Proceedings of the Second VLDB Workshop on Data Mining in Bioinformatics, Vienna, Austria, 2007.

3. Strong-association-rule mining for large-scale gene-expression data analysis: a case study on human SAGE data.;Becquet;Genome Biol.,2002

4. An association rule mining approach for co-regulated signature genes identification in cancer;Seeja;J. Circuits. Syst. Comput.,2009

5. Barry Becker,Ron Kohavi,Dan Sommerfield, Visualizing the simple Baysian classifier, in: Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann Publishers,pp. 237 - 249 ( 2001).

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