Relevance Vector Machine (RVM) Algorithm

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A Relevance Vector Machine (RVM) Algorithm is a probabilistic supervised learning algorithm that uses Bayesian inference...



References

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  • (Bishop, 2004) ⇒ Christopher M. Bishop. (2004). “Recent Advances in Bayesian Inference Techniques." Keynote Presentation at SIAM Conference on Data Mining.
    • Relevance Vector Machine (Tipping, 1999)
      • Bayesian alternative to support vector machine (SVM)
      • Properties
        • comparable error rates to SVM on new data
        • no cross-validation to set complexity parameters
        • applicable to wide choice of basis function
        • multi-class classification
        • probabilistic outputs
        • dramatically fewer kernels (by an order of magnitude)
        • but, slower to train than SVM

2001

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2000b

  1. D. J. C. Mackay. Bayesian non-linear modelling for the prediction competition. In ASHRAE Transactions, vol. 100, pages 1053- 1062. ASHRAE, Atlanta, Georgia, 1994.
  2. R. M. Neal. Bayesian Learning for Neural Networks. Springer, New York, 1996