First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) (2007)
Sept. 20, 2007 to Sept. 21, 2007
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.57
Burak Turhan , Bogazici University, Turkey
Onur Kutlubay , Bogazici University, Turkey
Ayse Bener , Bogazici University, Turkey
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.
A. Bener, O. Kutlubay and B. Turhan, "Evaluation of Feature Extraction Methods on Software Cost Estimation," 2007 First International Symposium on Empirical Software Engineering and Measurement(ESEM), Madrid, 2007, pp. 497.