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- W51487941 abstract "AbstractContrast sets have been shown to be a useful mechanism for describing differences between groups. A contrast set is a conjunction of attribute-value pairs that differ significantly in their distribution across groups. These groups are defined by a selected property that distinguishes one from the other (e.g customers who default on their mortgage versus those that don’t). In this paper, we propose a new search algorithm which uses a vertical approach for mining maximal contrast sets on categorical and quantitative data. We utilize a novel yet simple discretization technique, akin to simple binning, for continuous-valued attributes. Our experiments on real datasets demonstrate that our approach is more efficient than two previously proposed algorithms, and more effective in filtering interesting contrast sets.KeywordsMinimum SupportQuantitative AttributeMaximal GroupDiscovery TaskVertical ApproachThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W51487941 created "2016-06-24" @default.
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- W51487941 date "2011-01-01" @default.
- W51487941 modified "2023-10-17" @default.
- W51487941 title "COSINE: A Vertical Group Difference Approach to Contrast Set Mining" @default.
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- W51487941 doi "https://doi.org/10.1007/978-3-642-21043-3_43" @default.
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