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Erschienen in:
2005 | OriginalPaper | Buchkapitel
A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set
verfasst von : T.Y. Lin
Erschienen in: Foundations and Advances in Data Mining
Verlag: Springer Berlin Heidelberg
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A correct selection of features (attributes) is vital in data mining. For this aim, the complete set of features is constructed. Here are some important results: (1) Isomorphic relational tables have isomorphic patterns. Such an isomorphism classifies relational tables into isomorphic classes. (2) A unique canonical model for each isomorphic class is constructed; the canonical model is the bitmap indexes or its variants. (3) All possible features (attributes) is generated in the canonical model. (4) Through isomorphism theorem, all un-interpreted features of any table can be obtained.