Evaluating Performance of Some Classification Algorithms in Neural Networks
Kanadam Karteeka Pavan, Andhra Pradesh · 2014
Classification is a form of data analysis that extracts models describing important data classes, such models also called classifiers. In this paper an attempt is made for evaluating the performance of three neural network classifiers viz., Radial Basis Function, Multi Layer Perceptron and Probabilistic Neural Network. These classifiers are evaluated based on seven class wise (labels) and overall accuracy measures viz., Accuracy, Precession, Sensitivity, Specificity, Negative Predicted Value, F-measure and Mathews Correlation Coefficient. The results and conclusions obtained empirically are given in section 6.