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Associative Classification

  • Associative classification: Major steps
    • Mine data to find strong associations between frequent patterns (conjunctions of attribute-value pairs) and class labels
    • Association rules are generated in the form of
        • P1 ^ p2 … ^ pl →“Aclass = C” (conf, sup)
    • Organize the rules to form a rule-based classifier
  • Why effective?
    • It explores highly confident associations among multiple attributes and may overcome some constraints introduced by decision-tree induction, which considers only one attribute at a time
    • Associative classification has been found to be often more accurate than some traditional classification methods, such as C4.5

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