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» Semi-Naive Bayesian Classifier
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ECML
2007
Springer
14 years 1 months ago
Avoiding Boosting Overfitting by Removing Confusing Samples
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
Alexander Vezhnevets, Olga Barinova
AUSAI
2004
Springer
14 years 27 days ago
BayesTH-MCRDR Algorithm for Automatic Classification of Web Document
Nowadays, automated Web document classification is considered as an important method to manage and process an enormous amount of Web documents in digital forms that are extensive a...
Woo-Chul Cho, Debbie Richards
FLAIRS
2004
13 years 9 months ago
Personalization Using Hybrid Data Mining Approaches in E-Business Applications
Effective personalization is greatly demanded in highly heterogeneous and diverse e-commerce domain. In our approach we rely on the idea that an effective personalization techniqu...
Olena Parkhomenko, Yugyung Lee, Chintan Patel
COLING
2000
13 years 8 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Gerald Chao, Michael G. Dyer
CVPR
2003
IEEE
14 years 9 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman