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Mining Predictive k-CNF Expressions
May 2010 (vol. 22 no. 5)
pp. 743-748
Anton Dries, Katholieke Universiteit Leuven, Leuven
Luc De Raedt, Katholieke Universiteit Leuven, Leuven
Siegfried Nijssen, Katholieke Universiteit Leuven, Leuven
We adapt Mitchell's version space algorithm for mining k-CNF formulas. Advantages of this algorithm are that it runs in a single pass over the data, is conceptually simple, can be used for missing value prediction, and has interesting theoretical properties, while an empirical evaluation on classification tasks yields competitive predictive results.

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Index Terms:
Concept learning, machine learning, data mining.
Citation:
Anton Dries, Luc De Raedt, Siegfried Nijssen, "Mining Predictive k-CNF Expressions," IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 5, pp. 743-748, May 2010, doi:10.1109/TKDE.2009.152
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