文件名称:Bpriori_0
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在数据库中发现频繁模式和关联规则是数据挖掘领域的最基本、最重要的问题。大多数早期的研究采用了类似Apriori算法的产生候选级并测试迭代的途径代价是昂贵的，尤其是挖掘富模式和长模式时，Jiawei Han提出了一种新颖的数据结构FP_tree,及基于其上的FP_growth算法，主要用于有效的进行长模式与富模式的挖掘.本文在讨论了FP_growth算法的基础上，提出了用Visual C++实现该算法的方法，并编写了算法的程序。-found in the database model and the frequent association rules is the area of data mining the most fundamental and important issues. Most of the early studies used a similar Apriori algorithm for the selection of candidates and test-iterative way was costly, particularly mining the rich patterns and long model, Jiawei Han proposed a novel data structure FP_tree and on the basis of their FP_growth algorithm used effectively the model for long and rich patterns of excavation. This paper discussed the FP_growth algorithm on the basis of the Visual C of the algorithm, and the preparation procedure of the algorithm.
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压缩包 : 65520779bpriori_0.zip 列表 Apriori.class Copyable.class FastVector$FastVectorEnumeration.class FastVector.class FileOpr.class GetSource.class Item.class META-INF/ META-INF/MANIFEST.MF MyApp$1.class MyApp.class Output.class