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Abstract: Subgroup discovery is a learning task that aims at finding interesting rules from classified examples. The search is guided by a utility function, trading o# the coverage of rules against their statistical unusualness. One shortcoming of existing approaches is that they do not incorporate prior knowledge. To this end a novel generic sampling strategy is proposed. It allows to turn pattern mining into an iterative process. In each iteration the focus of subgroup discovery lies on those patterns... (Update)
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BibTeX entry: (Update)
@misc{ artificial-samplingbased,
author = "Martin Scholz Artificial",
title = "Sampling-Based Sequential Subgroup Mining",
url = "citeseer.ist.psu.edu/765771.html" }
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