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Using IF-THEN Rules for Classification

  • Represent the knowledge in the form of IF-THEN rules
    • R: IF age = youth AND student = yes THEN buys_computer = yes
    • Rule antecedent/precondition vs. rule consequent
  • Assessment of a rule: coverage and accuracy
    • ncovers = # of tuples covered by R
    • ncorrect = # of tuples correctly classified by R
    • coverage(R) = ncovers /|D| /* D: training data set */
    • accuracy(R) = ncorrect / ncovers
  • If more than one rule are triggered, need conflict resolution
    • Size ordering: assign the highest priority to the triggering rules that has the “toughest” requirement (i.e., with the most attribute tests)
    • Class-based ordering: decreasing order of prevalence or misclassification cost per class
    • Rule-based ordering (decision list): rules are organized into one long priority list, according to some measure of rule quality or by experts

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