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On Learning Software Effort Estimation
Sidra Tariq1; Muhammad Usman1; Raymond Wong2; Yan Zhuang3; Simon Fong3
2016-01-14
Conference Name2015 3rd International Symposium on Computational and Business Intelligence
Source PublicationProceedings - 2015 3rd International Symposium on Computational and Business Intelligence, ISCBI 2015
Pages79-84
Conference Date7-9 Dec. 2015
Conference PlaceBali, Indonesia
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

Software Effort is defined as the person months required to make a software application. Software effort estimation is usually the most important phase in the software development life cycle. Software effort estimation requires high accuracy at early phases, but accurate estimations are difficult to achieve. Machine Learning techniques are widely exploited that assist in getting improved evaluated values. In this paper we review, analyze and evaluate the work done in this area. This paper highlights general overview of effort estimation using different machine learning techniques containing latest trends in this field. Introducing the new approach is supportive for the reduction of cost and effort. The performance of the proposed method is evaluated to compute the project effort and comparison based on the parameters such as Correct-Percent, Mean Absolute Error (MAE), Root Mean Absolute Error (RMAE) and Relative Absolute Error (RAE).

KeywordAttribute Selection Effort Estimation Machine Learning Techniques Pre-processin Weka
DOIhttps://doi.org/10.1109/ISCBI.2015.21
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods
WOS IDWOS:000374594000005
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Citation statistics
Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computing, SZABIST-Islamabad, Pakistan
2.School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
3.Department of Computer and Information Science, University of Macau, Macau SAR
Recommended Citation
GB/T 7714
Sidra Tariq,Muhammad Usman,Raymond Wong,et al. On Learning Software Effort Estimation[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2016:79-84.
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