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Scaling RVMs for Text Classification

  • Catarina Silva
  • Bernardete Ribeiro
Part of the Studies in Computational Intelligence book series (SCI, volume 255)

Abstract

In the previous chapter we investigated learning techniques to improve support vector machines’ (SVMs) performance in text classification.We turn our attention in this chapter to relevance vector machines (RVMs) and their application to text classification. RVMs’ probabilistic Bayesian nature allows both predictive distributions on testing instances and model-based selection that yields a parsimonious solution. However, scaling up the algorithm is not viable in most digital information processing applications.

Keywords

Active Learning Linear Kernel Relevance Vector Machine AdaBoost Algorithm Training Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Catarina Silva
    • Bernardete Ribeiro

      There are no affiliations available

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