147 search results - page 18 / 30 » Agnostic Learning with Ensembles of Classifiers |
CISISSPAIN
2011
13 years 16 hour ago
2011
In last decades there have been many proposals from the machine learning community in the intrusion detection field. One of the main problems that Intrusion Detection Systems (IDSs...
ECML
2005
Springer
14 years 2 months ago
2005
Springer
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
ISDA
2010
IEEE
13 years 6 months ago
2010
IEEE
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
IJSI
2008
13 years 8 months ago
2008
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
DIS
2004
Springer
14 years 5 days ago
2004
Springer
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....