Application Of Dimensionality Reduction On Classification Of Colon Cancer Using Ica And K-Nn Algorithm
Journal Title: Annals. Computer Science Series - Year 2018, Vol 16, Issue 1
Abstract
Several sectors including engineering, health, academics and so on deals with very large number of information and few specimens. This highlight the need of a technique to improve data accuracy in order to enable professionals such as biologists, clinicians and so on to comprehend the structure of a complex microarray dataset and the gene expression in cells when reduced. This study employs Independent Component Analysis for feature extraction before using k-Nearest Neighbor algorithm to classify colon cancer dataset which contains DNA microarray gene expression data with 2000 features and 62 samples. The experiment was performed using MATLAB 2015a. The result shows that the dimensionality reduction applied improve the classification performance in terms of accuracy, sensitivity, specificity and precision by 11.3%, 25.2%, 36.3% and 12.8% respectively.
Authors and Affiliations
Rasheed Gbenga JIMOH, Ridwan Moyosore YUSUF, Yusuf Owolabi OLATUNDE, Yakub Kayode SAHEED
Keywords
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