File(s) under permanent embargo
A novel online Bayes classifier
conference contribution
posted on 2016-01-01, 00:00 authored by T T T Nguyen, T T Nguyen, X C Pham, A W C Liew, Y Hu, T Liang, Chang-Tsun LiChang-Tsun LiWe present VIGO, a novel online Bayesian classifier for both binary or multiclass problems. In our model, variational inference for multivariate Gaussian distribution technique is exploited to approximate the class conditional probability density functions of data in an online manner. Besides being a conservative learner with a low number of updates compared with many other popular algorithms, VIGO algorithm can be updated in a minibatch of an arbitrary size which makes it robust with noise data. Experiments over a large number of UCI datasets demonstrate the advantage of VIGO with many state-of-the-art methods presented in LIBOL - a prevalent library for online learning algorithms.
History
Event
International Association for Pattern Recognition. Conference (2016 : Gold Coast, Qld.)Series
International Association for Pattern Recognition ConferencePagination
1 - 6Publisher
Institute of Electrical and Electroncs EngineersLocation
Gold Coast, Qld.Place of publication
Piscataway, N.J.Publisher DOI
Start date
2016-11-30End date
2016-12-02ISBN-13
9781509028962Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2016, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
DICTA 2016 : Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and ApplicationsUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC