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Rule Induction: Sequential Covering Method

  • Sequential covering algorithm: Extracts rules directly from training data
  • Typical sequential covering algorithms: FOIL, AQ, CN2, RIPPER
  • Rules are learned sequentially, each for a given class Ci will cover many tuples of Ci but none (or few) of the tuples of other classes
  • Steps:
    • Rules are learned one at a time
    • Each time a rule is learned, the tuples covered by the rules are removed
    • Repeat the process on the remaining tuples until termination condition, e.g., when no more training examples or when the quality of a rule returned is below a user-specified threshold
  • Comp. w. decision-tree induction: learning a set of rules simultaneously

Speaker notes:

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