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 -