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A Comparative Performance Survey on Microarray Data Analysis Techniques for Colon Cancer Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 93 - Number 17 |
| Year of Publication: 2014 |
| Authors: Kshipra Chitode, Meghana Nagori |
10.5120/16430-6190
|
Kshipra Chitode, Meghana Nagori . A Comparative Performance Survey on Microarray Data Analysis Techniques for Colon Cancer Classification. International Journal of Computer Applications. 93, 17 ( May 2014), 28-34. DOI=10.5120/16430-6190
Abstract
The genetic information of any human beings is very helpful in cancer diagnosis. DNA microarray technology has enabled us to handle thousands of genes simultaneously. cDNA and Affymetrix microarray are the microarray technologies. The microarray data analysis can be done in supervised or unsupervised learning methods. Hierarchical clustering, k-means algorithms are widely used for clustering. As Curse of dimensionality is main challenge for microarray, Feature selection techniques are used. The classification accuracy depends on the feature selection technique used. In proposed work, feature selection techniques implemented are Signal-to-Noise ratio, Information Gain and Fishers criteria. SVM and KNN classifiers are built. The comparative results of performance accuracies are generated. The SVM classifier outperforms with fishers criteria and KNN outperforms with SNR.
References
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