Hybrid Intelligent System via Fuzzy Regression Analysis, Bayesian Gaussian Reasoning Model in Healthcare
Shailendra Singh Kathait, Dr Aankita Kaur, Anubha Varshney
In this paper, we propose the architecture of Hybrid Intelligent System with different techniques of pattern recognition and machine learning. Fuzzy Regression and Bayesian Gaussian Neural Network approach are used to build the model. Fuzzy regression deals with the uncertain, vagueness of the system. Naive Bayesian classiﬁer helps in building strong independent relationships whereas Gaussian classiﬁers correlates high dimensional data with kernel function to yield better performance of the system. A hybridized combined approach of neural network is presented in healthcare. It is due to its ﬂexibility of modeling, and robust nature, learning ability from complex functions and the application of different algorithm for reduction of errors for a better intelligent system.