313 search results - page 4 / 63 » Boosting with Diverse Base Classifiers |
DIS
2010
Springer
14 years 8 months ago
2010
Springer
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
ADMA
2006
Springer
14 years 11 months ago
2006
Springer
This paper presents a study on the combination of different classifiers for toxicity prediction. Two combination operators for the Multiple-Classifier System definition are also pr...
PAKDD
2000
ACM
15 years 1 months ago
2000
ACM
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
CIARP
2007
Springer
15 years 1 months ago
2007
Springer
Abstract. Diversity is a key characteristic to obtain advantages of combining predictors. In this paper, we propose a modification of bagging to explicitly trade off diversity and ...
SSPR
2000
Springer
15 years 1 months ago
2000
Springer
To improve weak classifiers bagging and boosting could be used. These techniques are based on combining classifiers. Usually, a simple majority vote or a weighted majority vote are...