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Bayesian Classification: Why?

  • A statistical classifier: performs probabilistic prediction, i.e., predicts class membership probabilities
  • Foundation: Based on Bayes’ Theorem.
  • Performance: A simple Bayesian classifier, naïve Bayesian classifier, has comparable performance with decision tree and selected neural network classifiers
  • Incremental: Each training example can incrementally increase/decrease the probability that a hypothesis is correct — prior knowledge can be combined with observed data
  • Standard: Even when Bayesian methods are computationally intractable, they can provide a standard of optimal decision making against which other methods can be measured

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