41 search results - page 2 / 9 » Practical Bias Variance Decomposition |
IWANN
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. In Machine Learning, ensembles are combination of classifiers. Their objective is to improve the accuracy. In previous works, we have presented a method for the generati...
BMCBI
2006
13 years 5 months ago
2006
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
ANSS
1996
IEEE
13 years 10 months ago
1996
IEEE
The asymptotic bias and variance are important determinants of the quality of a simulation run. In particular, the asymptotic bias can be used to approximate the bias introduced b...
CSDA
2008
13 years 5 months ago
2008
We derive second-order expressions for the asymptotic bias and variance of the log relative incidence estimator for the self-controlled case series method in a simplified scenario...
JMLR
2010
13 years 17 days ago
2010
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...