Minimizing the effects of overfitting and collinearity in construction cost estimation : a new hybird approach
Contribuinte(s) |
Golparvar-Fard, Mani Ham, Youngjib |
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Data(s) |
19/05/2014
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Resumo |
Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results. Research objective and method: A hybrid approach of Akaike information criterion (AIC) stepwise regression and principal component regression (PCR) is proposed to help solve overfitting and collinearity problems. Utilization of this approach in linear regression is validated by comparing it with other commonly used approaches. The mean square error obtained by leave-one-out cross validation (MSELOOCV) is used in model selection in deciding predictive variables. |
Identificador | |
Publicador |
2014 Construction Research Congress |
Relação |
http://issuu.com/manigolparvarfard/docs/2014crc_postersessionproceedings Xiong, Bo (2014) Minimizing the effects of overfitting and collinearity in construction cost estimation : a new hybird approach. In Golparvar-Fard, Mani & Ham, Youngjib (Eds.) 2014 Construction Research Congress, 19 May 2014, Atlanta, Georgia. |
Fonte |
School of Civil Engineering & Built Environment; Science & Engineering Faculty |
Palavras-Chave | #120201 Building Construction Management and Project Planning #120203 Quantity Surveying |
Tipo |
Conference Item |