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Propositionalization-based relational subgroup discovery with RSD
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DOI：10.1007/s10994-006-5834-0.png)
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摘要
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Relational rule learning algorithms are typically designed to construct classification and prediction rules. However, relational rule learning can be adapted also to subgroup discovery. This paper proposes a propositionalization approach to relational subgroup discovery, achieved through appropriately adapting rule learning and first-order feature construction. The proposed approach was successfully applied to standard ILP problems (East-West trains, King-Rook-King chess endgame and mutagenicity prediction) and two real-life problems (analysis of telephone calls and traffic accident analysis).
Keyword:
relational data mining
propositionalization
feature construction
subgroup discovery
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2.9
论文数:
2.7K
被引数:
3.4W
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