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) |
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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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