Hybrid Neuro-Fuzzy Classification Algorithm for Social Network
Anu Sharma1, M.K Sharma2, R.K Dwivedi3

1Anu Sharma Uttrakhand Technical University Dehradaun, India
2Dr. M.K Sharma Amrapali Institute Haldwani, India.
3Dr. R.K Dwivedi, Teerthanker Mahaveer University, Moradabad, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2434-2437 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8537088619/2019©BEIESP | DOI: 10.35940/ijeat.F8537.088619
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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: People tend to build and maintain their friendship relying on SNS nowadays. Thus, the problem of how to organize the social network accurately and automatically. In this paper, a hybrid neuro-fuzzy approach is used. . Many aspect impact the error values like input/output, membership functions, the training data arrays, and the number of epochs needed to train the model. This paper is based on hybrid Neuro-Fuzzy concept for testing the link prediction for facebook data. We use Matlab to calculate average testing Error, View Generation Rule, Output Surface.
Keywords: Neuro-Fuzzy Approach, Social Networks, MATLAB, Fuzzy Rule, Neural Network