Letters: Estimation of software project effort with support vector regression

Authors:
Adriano L. I. Oliveira
Affiliations:
Department of Computing Systems, Polytechnic School of Engineering, Pernambuco State University, Rua Benfica, 455, Madalena, 50.750-410 Recife - PE, Brazil
Venue:
Neurocomputing
Year:
2006

Citing 8
Cited 21

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Abstract

This paper provides a comparative study on support vector regression (SVR), radial basis functions neural networks (RBFNs) and linear regression for estimation of software project effort. We have considered SVR with linear as well as RBF kernels. The experiments were carried out using a dataset of software projects from NASA and the results have shown that SVR significantly outperforms RBFNs and linear regression in this task.