Fuzzy Clustering Systems in Analyzing High Dimensional Database
Article No.: 36, Pages 1 - 4
Abstract
Finding the division between malignant pleural mesothelioma (MPM) and adenocarcinoma (ADCA) from the gene expression of lung cancer database is difficult due to its high-dimensionality gene with noise. This paper proposes novel effective fuzzy soft clustering systems with the combination of possibilistic c-means to distinct the MPM and ADCA accurately gene expression ratios of lung cancer database. Since the proposed method is capable in clustering highly correlated gene expression of lung cancer database, first time all 181 tissue samples are used for finding MPM and ADCA during the experimental works using the proposed method. The performance of proposed method in clustering the Lung cancer database is shown through the clustering accuracy and error matrix.
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Published In
October 2015
381 pages
ISBN:9781450337359
DOI:10.1145/2818869
Copyright © 2015 ACM.
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Published: 07 October 2015
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