When Will It Be Done? Machine Learner Answers to the 300-Billion-Dollar Question

IEEE Intelligent Systems

Volumn 18, Issue 3, 2003, Pages 48-50

  Boetticher, Gary D ^a  

^a UNIVERSITY OF HOUSTON CLEAR LAKE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA MINING; LEARNING SYSTEMS;

SOFTWARE ESTIMATION;

SOFTWARE ENGINEERING;

EID: 0141718461     PISSN: 15411672     EISSN: None     Source Type: Journal    
DOI: 10.1109/MIS.2003.1200728     Document Type: Article

References (7)

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2. B. Boehm, Software Engineering Economics, Prentice-Hall, 1981.
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4. G. Boetticher, “Applying Machine Learners to GUI Specifications in Formulating Early Life Cycle Project Estimations,” Software Eng. with Computational Intelligence, T.M. Khoshgoftaar, ed., Kluwer Academic Publishers, 2003.
5. G. Wittig and G. Finnie, “Estimating Software Development Effort with Connectionist Models,” Information and Software Technology, vol. 39, no.7, 1997, pp. 469-476.
6. S. Chulani, B. Boehm, and B. Steece, “Bayesian Analysis of Empirical Software Engineering Cost Models,” IEEE Trans. Software Eng., vol. 25, no. 4, July/Aug. 1999, pp. 573-583.
7. S.E. Fahlman, An Empirical Study of Learning Speed in Back-Propagation Networks, tech. report CMU-CS-88-162, Dept. of Computer Science, Carnegie Mellon Univ., 1988.