Article ID Journal Published Year Pages File Type
10367094 Information and Software Technology 2013 16 Pages PDF
Abstract
Local bias in cross-company data does harm model calibration and adds noisy factors to model maintenance. The proposed local bias measure offers a means to quantify degree of local bias associated with a cross-company dataset, and assess its influence on parametric model performance. The local bias based weighted sampling technique can be applied to trade-off and mitigate potential risk of significant local bias, which limits the usability of cross-company data for general parametric model calibration and maintenance.
Related Topics
Physical Sciences and Engineering Computer Science Human-Computer Interaction
Authors
, , , , , , ,