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» Learning of Boolean Functions Using Support Vector Machines
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ECML
2006
Springer
14 years 24 days ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
TKDE
2008
123views more  TKDE 2008»
13 years 9 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
ICPR
2008
IEEE
14 years 3 months ago
Spam filtering with several novel bayesian classifiers
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...
Chuanliang Chen, Yingjie Tian, Chunhua Zhang
SIGIR
2008
ACM
13 years 9 months ago
Semi-supervised spam filtering: does it work?
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...
Mona Mojdeh, Gordon V. Cormack
PR
2008
91views more  PR 2008»
13 years 9 months ago
Applying the multi-category learning to multiple video object extraction
Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem....
Yi Liu, Yuan F. Zheng, Xiaotong Shen