Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Abstract. The use of support vector machines for multi-category problems is still an open field to research. Most of the published works use the one-against-rest strategy, but with...
This paper introduces a system that automatically classifies registration problems based on the type of registration required. Rather than rely on a single "best" algorit...
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...