293 search results - page 41 / 59 » Methods for learning classifier combinations: no clear winne... |
ICML
1998
IEEE
14 years 10 months ago
1998
IEEE
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
KDD
2009
ACM
14 years 9 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
ECCV
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
MICCAI
2000
Springer
14 years 23 days ago
2000
Springer
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
JMLR
2002
13 years 8 months ago
2002
In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...