Software effort estimation: Harmonizing algorithms and domain knowledge in an integrated data mining approach
Purvis, Martin; Deng, Jeremiah D.; Purvis, Maryam A.

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Purvis, M., Deng, J. D., & Purvis, M. A. (2009). Software effort estimation: Harmonizing algorithms and domain knowledge in an integrated data mining approach (Information Science Discussion Papers Series No. 2009/05). University of Otago. Retrieved from http://hdl.handle.net/10523/971
Permanent link to OUR Archive version:
http://hdl.handle.net/10523/971
Abstract:
Software development effort estimation is important for quality management in the software development industry, yet its automation still remains a challenging issue. Applying machine learning algorithms alone often can not achieve satisfactory results. In this paper, we present an integrated data mining framework that incorporates domain knowledge into a series of data analysis and modeling processes, including visualization, feature selection, and model validation. An empirical study on the software effort estimation problem using a benchmark dataset shows the effectiveness of the proposed approach.
Date:
2009-06
Publisher:
University of Otago
Pages:
15
Series number:
2009/05
Keywords:
software effort estimation; machine learning
Research Type:
Discussion Paper