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AIIA
2005
Springer

Mining Relational Association Rules for Propositional Classification

10 years 8 months ago
Mining Relational Association Rules for Propositional Classification
In traditional classification setting, training data are represented as a single table, where each row corresponds to an example and each column to a predictor variable or the target variable. However, this propositional (featurebased) representation is quite restrictive when data are organized into several tables of a database. In principle, relational data can be transformed into propositional one by constructing propositional features and performing classification according to some robust and well-known propositional classification methods. Since propositional features should capture relational properties of examples, multi-relational association rules can be adopted in feature construction. Propositionalisation based on relational association rules discovery is implemented in a relational classification framework, named MSRC, tightly integrated with a relational database. It performs the classification at different granularity levels and takes advantage from domain specific knowled...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where AIIA
Authors Annalisa Appice, Michelangelo Ceci, Donato Malerba
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