Learning Rules from Very Large Databases: A Rough Multiset Approach
نویسنده
چکیده
This paper presents a mechanism LERS-M for learning production rules from very large databases. The task of learning is formulated by the concept of multiset decision tables based on rough multisets and information multisystems. LERS-M is tightly coupled with object-relational database systems, and it can also work on distributed database systems.
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Distributed Incremental Data Mining from Very Large Databases: A Rough Multiset Approach
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