From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms

@inproceedings{Frnkranz2004FromLT,
  title={From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms},
  author={Johannes F{\"u}rnkranz},
  booktitle={Local Pattern Detection},
  year={2004}
}
Separate-and-conquer or covering rule learning algorithms may be viewed as a technique for using local pattern discovery for generating a global theory. Local patterns are learned one at a time, and each pattern is evaluated in a local context, with respect to the number of positive and negative examples that it covers. Global context is provided by removing the examples that are covered by previous patterns before learning a new rule. In this paper, we discuss several research issues that… CONTINUE READING
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