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...
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...
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...
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. ...
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...