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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 w
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本人搜集并调试无错的 关于数据挖掘算法,JAVA 实现,里面包含测试数据集,apriori 算法2个,FP-TREE 一个,FP-GROWP 2个 聚类1个、CLUSTREAM 一个,C45、ID3 等,下载后在相应文件夹中有 部分测试数据集合-I collect and debug error-free data mining algorithms, JAVA realization, which contains a set of test data, apriori algorithm 2
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Fortunately, a pseudo code for this algorithm is available in Chapter 6 (sample chapter available for free download) of Introduction to Data Mining. Let's start with loading the example dataset used in the PDF and creating a binary matrix representat
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