Foetal State Determination Using Support Vector Machine and Firefly Optimisation

In recent days, it has been found that vast amount of data is available in medical field that aid the doctors in disease diagnosis. Data mining techniques have been applied to extract knowledge from these medical data so that disease prediction becomes easy. In this paper, cardiotocogram (CTG) data is classified using support vector machine (SVM). An optimised feature subset is produced using Firefly Algorithm (FFA) with SVM evaluation. The results show that the performance of classification is improved with the optimal reduced feature set than with full feature set.