Open AccessA robust approach to QMU, validation, and conservative prediction.
Author(s) -
Daniel J. Segalman,
Thomas L. Paez,
Lara E Bauman
Publication year - 2013
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1089986
Subject(s) - margin (machine learning) , computer science , systematic error , data mining , econometrics , algorithm , machine learning , statistics , mathematics
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