A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split (1996)

Cached

Download Links

by Michael Kearns
Venue:Neural Computation
Citations:23 - 0 self

Active Bibliography

109 An experimental and theoretical comparison of model selection methods. Machine Learning 27 – - 1997
10 Towards Robust Model Selection using Estimation and Approximation Error Bounds – - 1996
13 The Informational Complexity of Learning from Examples – - 1996
101 Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation – - 1997
3 Knowledge acquisition in statistical learning theory – - 1999
37 Preventing "Overfitting" of Cross-Validation Data – - 1997
2 Finite Sample Size Results for Robust Model Selection; Application to Neural Networks – - 1995
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – - 1998
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization – - 1998
c ○ 2002 Kluwer Academic Publishers. Manufactured in The Netherlands. Model Selection and Error Estimation ∗
75 Model Selection and Error Estimation – - 2001
37 Adaptive model selection using empirical complexities – - 1999
3 Estimating the Expected Error of Empirical Minimizers for Model Selection – - 1998
29 Nonparametric time series prediction through adaptive model selection – - 2000
48 On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions – - 1996
13 Learning by Canonical Smooth Estimation, Part II: Learning and Choice of Model Complexity
78 PAC-Bayesian Model Averaging – - 1999
4 A Scaling Law for the Validation-Set Training-Set Size Ratio – - 1997
9 Annealed Theories of Learning – - 1995