Boolean Rule Based Classification for Microarray Gene Expression Data
R. Vengatesh Kumar1, R. Lawrance2
1R.VengateshKumar, Research Scholar, Research & Development Centre, Bharathiar University, Coimbatore, (Tamil Nadu), India.
2R.Lawrance, Director, Department of Computer Applications, Ayya Nadar Janaki Ammal College, Sivakasi, (Tamil Nadu), India.
Manuscript received on 14 August 2019. | Revised Manuscript received on 19 August 2019. | Manuscript published on 30 September 2019. | PP: 5366-5370 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6100098319/2019©BEIESP | DOI: 10.35940/ijrte.C6100.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Microarray technology provides a way to identify the expression level of ten thousands of genes simultaneously. This is useful for prediction and decision for the cancer treatments. To analyze and classify the gene expression data is more complex task. The rule based classifications are used to simplify the task of classifying genes. In this paper, a novel Boolean Rule based Classification (BRC) algorithm has been proposed. The efficient and relevant Boolean rules are assisting in classifying the test data correctly by Boolean Rule based Classifier model. This model is useful for drug designers. The experimental results show that in many cases the Boolean rule based classification yields more accurate results than other classical approaches.
Keywords: Gene Expression, Gene Selection, k-Means, Discretization, Boolean Rule Based Classification.
Scope of the Article: Classification.