Software effort estimation: Harmonizing algorithms and domain knowledge in an integrated data mining approach
Purvis, Martin; Deng, Jeremiah D.; Purvis, Maryam A.
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.
Publisher: University of Otago
Series number: 2009/05
Keywords: software effort estimation; machine learning
Research Type: Discussion Paper