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- W2077442669 abstract "Supervised local pattern discovery aims to find subsets of a database with a high statistical unusualness in the distribution of a target attribute. Local pattern discovery is often used to generate a human-understandable representation of the most interesting dependencies in a data set. Hence, the more crisp and concise the output is, the better. Unfortunately, standard algorithm often produce very large and redundant outputs." @default.
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- W2077442669 date "2012-08-12" @default.
- W2077442669 modified "2023-10-01" @default.
- W2077442669 title "An enhanced relevance criterion for more concise supervised pattern discovery" @default.
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- W2077442669 doi "https://doi.org/10.1145/2339530.2339756" @default.
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