Feature selection from colon cancer dataset for cancer classification using Artificial Neural Network

Abstract

In the fast-growing field of medicine and its dynamic demand in research, a study that proves significant improvement to healthcare seems imperative especially when it is on cancer research. This research paved the way for such significant findings by the inclusion of feature selection as one of its major components. Feature selection has become a vital task to apply data mining algorithms effectively in the real-world problems for classification. The Feature selection has been the focus of interest for quite some time and much-completed work related to it. This study used feature selection for improving classification accuracy on the cancerous dataset. This study proposed Artificial Neural Network (ANN) for cancer classification by the feature selection on colon cancer dataset. The study used the best first search method in Weka tools for feature selection. The result of the experiment achieved 98.4 %, accuracy for cancer classification after feature selection by using the proposed algorithm. The result indicated that feature selection improves the classification accuracy based on the experiment conducted on the colon cancer dataset.