Estimation of prediction error by using K-fold cross-validation

Estimation of prediction accuracy is important when our aim is prediction. The training error is an easy estimate of prediction error, but it has a downward bias. On the other hand, K -fold cross-validation has an upward bias. The upward bias may be negligible in leave-one-out cross-validation, but...

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Bibliographic Details
Published in:	Statistics and computing Vol. 21; no. 2; pp. 137 - 146
Main Author:	Fushiki, Tadayoshi
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.04.2011
Subjects:	Accuracy Artificial Intelligence Bias Computation Error analysis Errors Estimates Mathematics and Statistics Probability and Statistics in Computer Science Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Training Bias correction fold cross-validation Large dataset Prediction error
ISSN:	0960-3174, 1573-1375
Online Access:	Get full text
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