Fuzzy Classification with Comprehensive Learning Gravitational Search Algorithm in Breast Tumor Detection
Indu Bala1, Anshu Malhotra2
1Indu Bala, Department of Applied Science, Northcap University, Gurgaon, India.
2Anshu Malhotra, Department of Applied Science, Northcap University, Gurgaon, India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 14 March 2019 | Manuscript published on 30 July 2019 | PP: 2688-2694 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2801078219/19©BEIESP | DOI: 10.35940/ijrte.B2801.078219
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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 research paper herewith presents an effectual diagnosis classification system using fuzzy classifier and a very efficient heuristics algorithm comprehensive learning gravitational search algorithm (CLGSA) which has a good ability to search and finding optimal solutions. The effectiveness of the proposed model is estimating on Wisconsin breast cancer data set available in the UCI Machine learning source in the University of California, Irvine. We testify the data over the parameters of classification of accurateness, sensitivity as well as specificity with a much better and more responsive 10-fold cross validation method, which is considered as a reliable diagnostics model in the medical field. Experiment results have clearly shown that the proposed approach will turn out to be a calculative and decisive medium for cancer detection in the field of medicine.
Index Terms: Comprehensive Learning Gravitational Search Algorithm, Fuzzy Classifier, Breast Cancer Diagnosis, Heuristic Optimization.
Scope of the Article: Classification