A Mining Algorithm of Weighted Maximum Frequent Itemsets
Nanyan Liu · Microelectronics & Computer · 2008
Association rules is an important branch of data mining domain.Discovering maximum frequent itemsets is a key problem in mining association rules.The algorithm of discovering maximum frequent itemsets had equal character in the database.It was not different in reality.FP-Tree(Frequent Pattern Tree)do not adapt to need.An effective algo- rithm based on weighted FP-Tree for mining weighted maximum frequent itemsets was presented.It was during the mining without generating candidate itemsets.The algorithm was analysed in an example.Experimental result showed that it had effective and excellent expanding.