Item Sets, in this case, are products that are purchased together that meet the minimum support and confidence.
条目集，在这种情况下是一起购买的符合最低支持度和可信度的产品。
Then mine the set and get all frequent class association rules that satisfy the minimum support.
然后对该事务集进行数据挖掘，找出所有的满足最小支持度的类别关联规则。
The single minimum support degree is used in the existing association rules mining methods mostly.
现有的关联规则挖掘方法中，大多采用单一的最小支持度。
To meet this purpose, the CLOSET algorithm was modified to obtain frequent close patterns according to a minimum support and a minimum suspicion degree.
为此，修改了CLOSET算法来按照最小支持度和最小怀疑度来得到频繁闭模式。
For specific sensitive rules and given minimum support and confidence, get the sensitive transactions needing to modify and make appropriate treatment on them.
针对特定的敏感规则以及给定的最小支持度和置信度，得到所需要修改的敏感事务并对其做适当的处理。
This paper also discusses how to set the optimal minimum support for the common association rules mining algorithm, which can guarantee the frequent items are the weighted frequent items' superset.
同时，给出了最优的最小支持度设定方法，保证了普通关联规则算法所产生的频繁集为加权频繁集的超集。
This paper also discusses how to set the optimal minimum support for the common association rules mining algorithm, which can guarantee the frequent items are the weighted frequent items' superset.
同时，给出了最优的最小支持度设定方法，保证了普通关联规则算法所产生的频繁集为加权频繁集的超集。
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