Microarray Data Classification using Artificial Neural Network
K. Kalyani
K Kalyani, Assistant Professor, Department of Computer Science, Marudupandiyar College of Arts and Science Affiliated to Bharathidasan University, Thanjavur (Tamil Nadu), India.
Manuscript received on 16 December 2019 | Revised Manuscript received on 24 December 2019 | Manuscript Published on 31 December 2019 | PP: 54-56 | Volume-9 Issue-1S2 December 2019 | Retrieval Number: A10571291S219/19©BEIESP | DOI: 10.35940/ijeat.A1057.1291S219
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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: The accurate cancer classification is very important task for cancer treatment. Recently the informative genes are identified from the thousands of genes for correct cancer classification. The collection of microscopic Deoxyribo Nucleic Acid (DNA) microarray is attached in the solid surface. In this study, DNA microarray data is used for cancer classification. The system uses Artificial Neural Network (ANN) for DNA Microarray Data Classification (MDC). Initially, the preprocessing step is made by using log transformation method to remove the raw data and feature selection. These selected features are classified by using ANN. REctified Linear Unit (RELU) activation function is used as the activation function in each ANN layer. Softmax is used for classification. The performance of the system is made by using leukemia dataset. MDC system produces the classification accuracy of 91.65% by using ANN.
Keywords: Microarray Data Classification, Flat Pattern Filtering, Feature Selection, Artificial Neural Network.
Scope of the Article: Classification