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A theory of cross-validation error

Turney, Peter D. (1994) A theory of cross-validation error. [Journal (Paginated)]

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Abstract

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.

Item Type:Journal (Paginated)
Subjects:Computer Science > Artificial Intelligence
Computer Science > Machine Learning
Computer Science > Statistical Models
ID Code:1820
Deposited By:Turney, Peter
Deposited On:13 Oct 2001
Last Modified:11 Mar 2011 08:54

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