417 search results - page 4 / 84 » Some Theory for Generalized Boosting Algorithms |
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
TIT
2002
13 years 7 months ago
2002
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
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...
PKDD
2005
Springer
14 years 1 months ago
2005
Springer
In most of the learning algorithms, examples in the training set are treated equally. Some examples, however, carry more reliable or critical information about the target than the ...
IDA
2002
Springer
13 years 7 months ago
2002
Springer
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...