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

Md Akizur Rahman, Ravie Chandren Muniyandi

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)1387-1393
Number of pages7
JournalInternational Journal on Advanced Science, Engineering and Information Technology
Volume8
Issue number4-2
Publication statusPublished - 1 Jan 2018

Fingerprint

colorectal neoplasms
Colonic Neoplasms
neural networks
Feature extraction
Neural networks
neoplasms
Neoplasms
Research
Data Mining
health services
medicine
Medicine
Datasets
Delivery of Health Care
Data mining
Experiments

Keywords

  • Artificial Neural Network
  • Cancer classification
  • Colon cancer
  • Feature selection

ASJC Scopus subject areas

  • Computer Science(all)
  • Agricultural and Biological Sciences(all)
  • Engineering(all)

Cite this

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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.",
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