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Success of data mining as an enterprise technology crucially depends on seamless integration of this technology with enterprise databases. In this paper, the authors describe basic of various data mining algorithms to use database as secondary storage in order to integrate data mining with database systems. The input to a data mining scheme is generally expressed as a table of independent instances of the concept to be learned. Because of this, it has been suggested, disparagingly, that they should really talk of file mining rather than database mining. Relational data is more complex than a flat file. A finite set of finite relations can always be recast into a single table, although often at enormous cost in space.
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