22 search results - page 1 / 5 » A bias variance decomposition for models using collective in... |
ILP
2007
Springer
13 years 11 months ago
2007
Springer
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
MCS
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Classifier decision fusion has been shown to act in a manner analogous to the back-projection of Radon transformations when individual classifier feature sets are non o...
ML
2008
ACM
13 years 5 months ago
2008
ACM
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
ANSS
1996
IEEE
13 years 9 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...
ICML
1997
IEEE
14 years 5 months ago
1997
IEEE
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...