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» A cloning approach to classifier training
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93
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ICML
2009
IEEE
16 years 1 months ago
Compositional noisy-logical learning
We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
Alan L. Yuille, Songfeng Zheng
MCS
2009
Springer
15 years 5 months ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar
UAI
2008
15 years 2 months ago
Small Sample Inference for Generalization Error in Classification Using the CUD Bound
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
Eric Laber, Susan Murphy
86
Voted
FLAIRS
2004
15 years 2 months ago
Highway Vehicle Classification by Probabilistic Neural Networks
The Federal Highway Administration (FHWA) Office of Highway Planning requires states to furnish vehicle classification data as part of the Highway Performance Monitoring Systems (...
Valerian Kwigizile, Majura F. Selekwa, Renatus N. ...
89
Voted
EACL
2006
ACL Anthology
15 years 2 months ago
Towards Robust Animacy Classification Using Morphosyntactic Distributional Features
This paper presents results from experiments in automatic classification of animacy for Norwegian nouns using decision-tree classifiers. The method makes use of relative frequency...
Lilja Øvrelid