Current Slide

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