Global Optimization of Analogy-Based Software Cost Estimation with Genetic Algorithms

Abstract : Estimation by Analogy is a popular method in the field of software cost estimation. A number of research approaches focus on optimizing the parameters of the method. This paper proposes an optimal global setup for determining empirically the best method parameter configuration based on genetic algorithms. We describe how such search can be performed, and in particular how spaces whose dimensions are of different type can be explored. We report results on two datasets and compare with approaches that explore partially the search space. Results provide evidence that our method produces similar or better accuracy figures with respect to other approaches.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.350-359, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_42〉
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Dimitrios Milios, Ioannis Stamelos, Christos Chatzibagias. Global Optimization of Analogy-Based Software Cost Estimation with Genetic Algorithms. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.350-359, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_42〉. 〈hal-01571483〉

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