A. Santhakumaran

Learn More
Many real world problems can be solved with Artificial Neural Networks in the areas of pattern recognition, signal processing and medical diagnosis. Most of the medical data set is seldom complete. Artificial Neural Networks require complete set of data for an accurate classification. This paper dwells on the various missing value techniques to improve the(More)
In this paper, we consider an M/G/1 retrial queue with Bernoulli feedback and general retrial times where the external arrivals blocked either with probability q join the infinite waiting room called non-retrial queue or with probability p, (p+q = 1) leave the service area and enter the retrial group called orbit in FIFO discipline. Also we assume that only(More)
— Breast cancer diagnosis has been approached by various machine learning techniques for many years. This paper presents a study on classification of Breast cancer using Feed Forward Artificial Neural Networks. Back propagation algorithm is used to train this network. The performance of the network is evaluated using Wisconsin breast cancer data set for(More)
Medicine has always benefited from the technology. Artificial Neural Networks is currently the promising area of interest to solve medical problems. Diagnosis of diabetes is one of the most challenging problems in machine learning. This medical data set is seldom complete. Artificial neural networks require complete set of data for an accurate(More)
  • 1