6 search results - page 1 / 2 » Bias and Variance of Rotation-Based Ensembles |
IWANN
2005
Springer
13 years 10 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...
ICPR
2000
IEEE
14 years 5 months ago
2000
IEEE
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
MCS
2010
Springer
13 years 6 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...
AAAI
2000
13 years 6 months ago
2000
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
MCS
2002
Springer
13 years 4 months ago
2002
Springer
Abstract. Boosting methods are known to improve generalization performances of learning algorithms reducing both bias and variance or enlarging the margin of the resulting multi-cl...