文件名称:newclass
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- 2012-11-26
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ne of themost popular datamining approaches is to fi nd frequent itemsets froma transaction
dataset and derive association rules. Finding frequent itemsets (itemsetswith frequency larger
than or equal to a user specifi ed minimum support) is not trivial because of its combinatorial
explosion. Once frequent itemsets are obtained, it is straightforward to generate association
rules with confi dence larger than or equal to a user specifi ed minimum confi dence
dataset and derive association rules. Finding frequent itemsets (itemsetswith frequency larger
than or equal to a user specifi ed minimum support) is not trivial because of its combinatorial
explosion. Once frequent itemsets are obtained, it is straightforward to generate association
rules with confi dence larger than or equal to a user specifi ed minimum confi dence
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新课程改革下计算机教学的反思.doc