A Fuzzy Based Classification – An Experimental Analysis
S.Leoni Sharmila1, C.Dharuman2, P.Venkatesan3
1S. Leoni Sharmila, Asst. Professor, Department of Mathematics, SRM IST, Ramapuram, Chennai.
2JC. Dharuman, Professor, Department of Mathematics, SRM IST, Ramapuram, Chennai.
3P.Venkatesan, Professor, Faculty of Research, Sri Ramachandra Medical College & Research Institute, Chennai.
Manuscript received on 01 August 2019 | Revised Manuscript received on 05 August 2019 | Manuscript published on 30 August 2019 | PP: 4634-4638 | Volume-8 Issue-10, August 2019 | Retrieval Number: J10650881019/2019©BEIESP | DOI: 10.35940/ijitee.J1065.0881019
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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: Soft Computing has become popular in developing systems that encloses human expertise. Imaging technologies and clinical cytology has improved in disease diagnosis. Exact detection is extremely important for proper treatment and cure of disease. Two soft computing technique Neural Network and Support Vector Machine are used for classification of Caridotocography data set. This paper clearly explains the advantages of hybrid technique, when Fuzzy is combined with Neural Network and Support Vector Machine it is clearly noticed that there is an increase in accuracy of classification rate.
Keywords: Neural Network, SVM, Fuzzy Neural Network, Fuzzy SVM.
Scope of the Article: Fuzzy Logics