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  1. Clark, P. and Boswell. R. (1991). Rule Induction With CN2: Some Recent Improvements. Proc. European Working Session on Learning (ESWL'91), Porto, Portugal. pp151-163.

  2. Quinlan, J. R. and Cameron-Jones, R. M. (1993). FOIL: A Midterm Report. Proc. ECML, Vienna, Austria, pp3-20.

  3. Yin, X. and Han, J. (2003). CPAR: Classification based on Predictive Association Rules. Proc. SIAM Int. Conf. on Data Mining (SDM'03), San Fransisco, CA, pp. 331-335.

  4. http://www.cxc.liv.ac.uk/~frans/KDD/Software/FOIL_PRM_CPAR/foil.html, Department of Computer Science, The University of Liverpool, UK.

  5. Let Var be the largest number of distinct variables for any clause in rule R, excluding the last conjunct. Let MaxP be the number of predicates with largest arity MaxA. Then an approximation of the number of nodes generated to learn R is: NodesSearched ≤ 2 * MaxP * (Var + MaxA – 1)MaxA , as shown in Pazzani and Kibler (1992).

  6. Michael Pazzani and Dennis Kibler. The Utility of Knowledge in Inductive Learning. Machine Learning, Volume 9, Number 1, 1992.

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