Improve software effort estimation using information entropy

Effort estimation is so important and determinative in
management and development of software projects. Most of the
approaches that have been proposed in software estimation are
suffered from low accuracy according to limitation of dataset's
samples. So, in this paper a hybrid method has been proposed in
order to increase the accuracy and decrease the time complexity.
In this way, a feature selection has been used before the main
methods to improve the accuracy and reduce feature space
complexity. Finally, hybrid method performances are promising
better result than other algorithms.