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Discriminative Classifiers

  • Advantages
    • Prediction accuracy is generally high
      • As compared to Bayesian methods – in general
    • Robust, works when training examples contain errors
    • Fast evaluation of the learned target function
      • Bayesian networks are normally slow
  • Criticism
    • Long training time
    • Difficult to understand the learned function (weights)
      • Bayesian networks can be used easily for pattern discovery
    • Not easy to incorporate domain knowledge
      • Easy in the form of priors on the data or distributions

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