Improving Accuracy of Integrated Neuro-Fuzzy Classifier with FCM based Clustering for Diagnosis of Psychiatric Disorder

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Autism spectrum disorder (ASD) neurodevelopment Clinical decision-making process complex. Due to complex nature of sign and its symptoms clinical decision making may lead misclassification. To deal with such medical problems methods or approaches soft computing play an important role. This paper will focus on presenting integrated Neuro-fuzzy model. model has the learning strength neural network knowledge representation ability fuzzy logic. Modified Adaptive Neuro –Fuzzy inference system (M-ANFIS) used here for classification predication. Here Fuzzy C-mean (FCM) Clustering first make classes data before in ANFIS. FCM based class reduce classifier computational overhead. Precision error recall, F-measure accuracy matrices are compare experimental results other classic methods.