TY  - GEN
ID  - cogprints1820
UR  - http://cogprints.org/1820/
A1  - Turney, Peter D.
Y1  - 1994///
N2  - This paper presents a theory of error in cross-validation testing of algorithms for predicting
real-valued attributes. The theory justifies the claim that predicting real-valued
attributes requires balancing the conflicting demands of simplicity and accuracy. Furthermore,
the theory indicates precisely how these conflicting demands must be balanced, in
order to minimize cross-validation error. A general theory is presented, then it is
developed in detail for linear regression and instance-based learning.
TI  - A theory of cross-validation error
SP  - 361
AV  - public
EP  - 391
ER  -

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