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Applying statistical methodology to optimize and simplify s..:

, In: Proceedings of the 2006 ACM symposium on Applied computing,

Wong, W. Eric ; Zhao, Jin ; Chan, Victor K. Y. - p. 1728-1733 , 2006

Link: https://dl.acm.org/doi/10.1145/1141277.1141687

RT 
T1 <cTitle>Proceedings of the 2006 ACM symposium on Applied computing</cTitle>: T1 <Title>Applying statistical methodology to optimize and simplify software metric models with missing data</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-1141687&Exemplar=1&LAN=DE
				
A1 Wong, W. Eric
A1 Zhao, Jin
A1 Chan, Victor K. Y.
PB ACM
YR 2006
K1 imputation method
K1 missing data
K1 model optimization
K1 model simplification
K1 models
K1 software metrics
K1 General and reference
K1 Cross-computing tools and techniques
K1 Metrics
K1 Computing methodologies
K1 Modeling and simulation
K1 Model development and analysis
K1 Mathematics of computing
K1 Probability and statistics
K1 Statistical paradigms
K1 Artificial intelligence
K1 Knowledge representation and reasoning
K1 Probabilistic reasoning
K1 Statistical graphics
K1 Model verification and validation
K1 Vagueness and fuzzy logic
SP 1728
OP 1733
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/1141277.1141687
DO https://dl.acm.org/doi/10.1145/1141277.1141687
SF ELIB - SuUB Bremen

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