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Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach

Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach

Jeremiah D. Deng, Martin Purvis, Maryam Purvis
Copyright: © 2011 |Volume: 7 |Issue: 3 |Pages: 13
ISSN: 1548-3657|EISSN: 1548-3665|EISBN13: 9781613507957|DOI: 10.4018/jiit.2011070104
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MLA

Deng, Jeremiah D., et al. "Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach." IJIIT vol.7, no.3 2011: pp.41-53. http://doi.org/10.4018/jiit.2011070104

APA

Deng, J. D., Purvis, M., & Purvis, M. (2011). Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach. International Journal of Intelligent Information Technologies (IJIIT), 7(3), 41-53. http://doi.org/10.4018/jiit.2011070104

Chicago

Deng, Jeremiah D., Martin Purvis, and Maryam Purvis. "Software Effort Estimation: Harmonizing Algorithms and Domain Knowledge in an Integrated Data Mining Approach," International Journal of Intelligent Information Technologies (IJIIT) 7, no.3: 41-53. http://doi.org/10.4018/jiit.2011070104

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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 cannot achieve satisfactory results. This paper presents 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 necessity and effectiveness of the proposed approach.

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