Incremental Reduced Error Pruning
نویسندگان
چکیده
This paper outlines some problems that may occur with Reduced Error Pruning in relational learning algorithms, most notably efficiency. Thereafter a new method, Incremental Reduced Error Pruning, is proposed that attempts to address all of these problems. Experiments show that in many noisy domains this method is much more efficient than alternative algorithms, along with a slight gain in accuracy. However, the experiments show as well that the use of the algorithm cannot be recommended for domains which require a very specific concept description.
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Incremental reduced error pruning is a technique that has been extensively used for efficient induction of ordered rule sets (decision lists). Several criteria have been developed regarding how to prune rules and whether or not to exclude generated rules. A version of incremental reduced error pruning for unordered rule sets is presented, and the appropriateness of previously proposed criteria ...
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