文件名称:Gg
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将FP-G rowth算法应用于面向目标的关联规则(OOA)挖掘,对FP-Tree的结点进行了修改,增加了目标支持度计数和效用度累计两个字段,对FP-G rowth算法进行了改进.实验结果表明,改进后的方法比基于Apriori算法和基于D free算法的OOA挖掘效率更高.
-The FP-G rowth algorithm is applied to a goal-oriented association rules (OOA) mining, on the FP-Tree nodes were modified to increase the target degree of support for the effectiveness of cumulative counts and two fields, the FP-G rowth algorithm is improved. The experimental results show that the improved approach is better than Apriori-based algorithm and D free algorithm OOA mining more efficient.
-The FP-G rowth algorithm is applied to a goal-oriented association rules (OOA) mining, on the FP-Tree nodes were modified to increase the target degree of support for the effectiveness of cumulative counts and two fields, the FP-G rowth algorithm is improved. The experimental results show that the improved approach is better than Apriori-based algorithm and D free algorithm OOA mining more efficient.
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Gg.cpp