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Application of Gamma Classifier to Development Effort Prediction of Software Projects |
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PP: 411-418 |
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Author(s) |
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Cuauhtemoc Lopez-Martın,
Itzama Lopez-Yanez,
Cornelio Yanez-Marquez,
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Abstract |
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| The Gamma Classifier is a novel algorithm, immersed in the Associative Approach to Pattern Recognition, of which the
Alpha-Beta BAM is another relevant model. The Gamma Classifier has shown competitive performance in areas such as prediction of
atmospheric pollutants, wireless network sensor location, and concrete mix properties forecast. This paper introduces the fist successful
application of this model to development effort prediction of software projects. In this sense, an ongoing concern of software managers
is to predict how many hours should be spent on a development project, mainly regarding project budgeting and planning. Software
managers based typically their predictions on judgment-based techniques; however, models-based techniques (statistical regressions,
fuzzy logic, neural networks, or genetic programming) offer a good alternative. In this study, the Gamma Classifier was trained with a
data set of 163 software projects and then used for predicting the effort of another data set integrated by 68 projects; all projects were
developed by 53 and 21 practitioners respectively. Accuracy result of this classifier was compared with that of a fuzzy logic model and
that from a statistical regression model. |
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