DOI Bookmark:
http://doi.ieeecomputersociety.org/10.1109/TKDE.2009.152
We adapt Mitchell's version space algorithm for mining k-CNF formulae. 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.
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, 24 Jun. 2009. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TKDE.2009.152>
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