SOFTWARE EFFORT ESTIMATION USING RADIAL BASIS FUNCTION NEURAL NETWORKS
Ana Maria Bautista, Ángel Castellanos, Tomás San Feliú · 2014
One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset. This paper evaluates and compares radial basis function versus a regression model. The results show that radial basis function neural network have obtained less Mean Square Error than the regression method.