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» Selection of Classifiers Based on Multiple Classifier Behavi...
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153
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ISF
2010
164views more  ISF 2010»
14 years 12 months ago
An SVM-based machine learning method for accurate internet traffic classification
Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven t...
Ruixi Yuan, Zhu Li, Xiaohong Guan, Li Xu
110
Voted
ICPR
2008
IEEE
16 years 3 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...
123
Voted
COLING
2002
15 years 2 months ago
Multi-Dimensional Text Classification
This paper proposes a multi-dimensional framework for classifying text documents. In this framework, the concept of multidimensional category model is introduced for representing ...
Thanaruk Theeramunkong, Verayuth Lertnattee
JMLR
2010
156views more  JMLR 2010»
14 years 9 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
176
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KDD
1998
ACM
442views Data Mining» more  KDD 1998»
15 years 6 months ago
BAYDA: Software for Bayesian Classification and Feature Selection
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Petri Kontkanen, Petri Myllymäki, Tomi Siland...