70 search results - page 4 / 14 » Using Generalization Error Bounds to Train the Set Covering ... |
ML
2002
ACM
13 years 7 months ago
2002
ACM
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
LWA
2004
13 years 9 months ago
2004
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
ACL
2006
13 years 9 months ago
2006
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
PR
2007
13 years 7 months ago
2007
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...