'Institute of Electrical and Electronics Engineers (IEEE)'
Abstract
In this paper, we present a medical decision support system based on a hybrid approach utilising rough sets and a probabilistic neural network. We utilised the ability of rough sets to perform dimensionality reduction to eliminate redundant attributes from a biomedical dataset. We then utilised a probabilistic neural network to perform supervised classification. Our results indicate that rough sets was able to reduce the number of attributes in the dataset by 67% without sacrificing classification accuracy. Our classification accuracy results yielded results on the order of 93%
