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Dimension Reduction of Gene Expression Data for Designing Optimized Rule Base Classifier

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Recent Advances in Information Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 266))

Abstract

The paper highlights the need of dimension reduction of voluminous gene expression microarray data for developing a robust classifier to predict patients with cancerous genes. The proposed algorithm builds a fuzzy rule based classifier with optimized rule set without much sacrificing classification accuracy. The gene expression matrix is first discretized using linguistic values. The importance factor of each gene is then evaluated representing the degree of presence of a unique linguistic value of the gene both in disease and nondisease classes. Initial fuzzy rule base consists higher ranking genes and gradually other genes are included in the rule base in order to achieve maximum classification accuracy. Thus optimum rule set is built with important genes for classification of test data set. The methodology proposed here has been successfully demonstrated for the lung cancer classification problem, which includes 97 smokers with lung cancer and 90 without lung cancer gene expression data. The results are promising even though maximum number of genes are removed from the original data.

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, St. Thomas College of Engineering and Technology, Khidirpore, India

    Amit Paul

  2. Computer Science and Technology, Bengal Engineering and Science University, Shibpur, India

    Jaya Sil

  3. Health Care Science and Technology, Bengal Engineering and Science University, Shibpur, India

    Chitrangada Das Mukhopadhyay

Authors
  1. Amit Paul
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  2. Jaya Sil
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  3. Chitrangada Das Mukhopadhyay
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Corresponding author

Correspondence to Amit Paul .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Indian School of Mines, Dhanbad, Dhanbad, Jharkhand, India

    G. P. Biswas

  2. Computer Science and Engineering, Indian School of Mines, Dhanbad, Dhanbad, Jharkhand, India

    Sushanta Mukhopadhyay

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© 2014 Springer India

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Paul, A., Sil, J., Das Mukhopadhyay, C. (2014). Dimension Reduction of Gene Expression Data for Designing Optimized Rule Base Classifier. In: Biswas, G., Mukhopadhyay, S. (eds) Recent Advances in Information Technology. Advances in Intelligent Systems and Computing, vol 266. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1856-2_15

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  • DOI: https://doi.org/10.1007/978-81-322-1856-2_15

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1855-5

  • Online ISBN: 978-81-322-1856-2

  • eBook Packages: EngineeringEngineering (R0)

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