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How to Learn-One-Rule?

  • Start with the most general rule possible: condition = empty
  • Adding new attributes by adopting a greedy depth-first strategy
    • Picks the one that most improves the rule quality
  • Rule-Quality measures: consider both coverage and accuracy
    • Foil-gain (in FOIL & RIPPER): assesses info_gain by extending condition

\[FOIL-Gain=pos{'} \times \left ( log_{2}\frac{pos'}{pos'+neg'}-log_{2}\frac{pos}{pos+neg} \right )\]

      • favors rules that have high accuracy and cover many positive tuples
  • Rule pruning based on an independent set of test tuples

\[FOIL-Prune(R)=\frac{pos-neg}{pos+neg} \right )\]

      • Pos/neg are # of positive/negative tuples covered by R.
      • If FOIL_Prune is higher for the pruned version of R, prune R

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