First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) Madrid, Spain September 20-September 21 ISBN: 0-7695-2886-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.57
This research investigates the effects of linear and non-linear feature extraction methods on the cost estimation performance. We use Principal Component Analysis (PCA) and Isomap for extracting new features from observed ones and evaluate these methods with support vector regression (SVR) on publicly available datasets. Our results for these datasets indicate there is no significant difference between the performances of these linear and non-linear feature extraction methods.
Citation:
Burak Turhan, Onur Kutlubay, Ayse Bener, "Evaluation of Feature Extraction Methods on Software Cost Estimation," esem, pp.497, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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