Comparing and identifying common factors in frequent item set algorithms in association rule

This paper is initiated from the observation of existing research work which is related in frequent Item Set mining algorithms such as MAFIA, FP -Growth, Transaction Mapping (TM) and ECLAT(Equivalence CLAss Transformation). As per the study of above mentioned algorithms all the items are counted the...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Clementking, A., Angel Latha Mary, S.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithms association rule mining Association rules Data mining Data warehouses Educational institutions frequent itemsets Information analysis Itemsets Machine learning algorithms Merging Statistics Transaction databases
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