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fpgrowth
相关语句
  fp-growth
     A study on the performance of the FP-growth method shows that it is efficient and scalable for mining both long and short frequent patterns, and is about an order of magnitude faster than the Apriori algorithm.
     对FP—growth算法的性能分析研究表明:对于挖掘长的和短的频繁模式,它都是有效的和可伸缩的,并且比Apriori算法快一个数量级。
短句来源
     Expense of such method is so prodigious that we brought forward a new algorithm called frequent-pattern growth (FP-growth).
     这种方法的代价是很大的。 为了解决这个问题,提出了相应的不产生侯选集的频繁集的FP—growth算法。
短句来源
     FP-growth mainly adopts a divide-and-conquer strategy to avoid huge sizes.
     FP—growth算法的优点是节省时间和空间,对大规模数据采用分治的方法以避免规模巨大难以接受。
短句来源
  相似匹配句对
     fp.
     fp.
短句来源
     A Study of Intrusion Detection Based on Algorithm of FP-Growth
     基于FP-Growth的入侵检测研究
短句来源
     An improvement to FP growth agorithm
     FP-growth算法的一种改进
短句来源
     FP ALGEBRA
     FP代数
短句来源
     FP-3 386 Mobile Data Processing System
     FP3386现场处理机
短句来源
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  fpgrowth
COFI is faster or as fast as FPGrowth and requires significantly less memory.
      
FPgrowth is about an order of magnitude faster than the Apriori.
      
On the three real-world datasets with low minimum supports, the ranking is always Charm > FPgrowth > Apriori > Closet.
      


In the course of data mining,the large scale candidate model is the bottle neck to limit the function of the system. To solve the problem,a new construction of data mining - FPtree and the corresponding construction algorithm - FPgrowth are presented.The experiment proved that all the frequent patterns of FPtree can be found by using this method.In addition,FPgrowth is more stable compared to the Aprior algorithm,and its operating speed is quicker,which comes up with a new developing thought...

In the course of data mining,the large scale candidate model is the bottle neck to limit the function of the system. To solve the problem,a new construction of data mining - FPtree and the corresponding construction algorithm - FPgrowth are presented.The experiment proved that all the frequent patterns of FPtree can be found by using this method.In addition,FPgrowth is more stable compared to the Aprior algorithm,and its operating speed is quicker,which comes up with a new developing thought to realize the data mining.

在数据挖掘中 ,规模巨大的候选模式是约束系统性能的瓶颈 ,为解决该问题 ,提出了一个新的数据挖掘结构FPtree及相应的构造算法FPgrowth .实验测试证明 ,利用FPgrowth算法可以发现FPtree中所有的强模式 .此外 ,与Aprior算法相比 ,该算法性能稳定 ,具有较高的运行效率 ,为数据挖掘技术的实现提出了一种新的思路 .

In this paper,an efficient algorithm,called PP(Pseudo Projection),is proposed to discover frequent patterns.PP represents subsets of transactions that support patterns by a tree based structure which avoids repetitive scans of databases and recursive materializations of transaction subsets.PP is one to three orders of magnitude efficient than Apriori and FPGrowth.Then,PP is extended into another efficient algorithm,called CRM PP,to mine classification rules.CRM PP pushes multiple minimum supports threshold...

In this paper,an efficient algorithm,called PP(Pseudo Projection),is proposed to discover frequent patterns.PP represents subsets of transactions that support patterns by a tree based structure which avoids repetitive scans of databases and recursive materializations of transaction subsets.PP is one to three orders of magnitude efficient than Apriori and FPGrowth.Then,PP is extended into another efficient algorithm,called CRM PP,to mine classification rules.CRM PP pushes multiple minimum supports threshold into the discovery stage of frequent patterns,and generates rules in the same stage.CRM PP is also one to three orders of magnitude efficient than algorithms derived from Apriori and FPGrowth.

本文首先提出了一种挖掘频集的高效算法PP。它采用了一种基于树的模式支持集表示 ,避免了反复扫描数据库和递归建造个数与频繁模式数相同的模式支持集 ,其效率比Apriori和FPGrowth高 1~ 3个数量级。PP被进一步扩展成发现分类规则的有效算法CRM PP。CRM PP将多支持率剪裁集成到频集发现阶段 ,将二阶段挖掘法改进为单阶段挖掘法。CRM PP的效率也比基于Apriori和FPGrowth的二阶段算法高 1~ 3个数量级

The effective mining frequent item sets is key problem in mining maximal frequent item sets. In order to overcome insufficiency of the Apriori algorithm on the mining maximal frequent item sets,and shortcoming of FP-Tree memory structure algorithm need many times traversal. This article has introduced an array technique,reduce the FP-Tree traversal time on mining frequent item sets so that the method can be sped up. And proposes by this based on the FP-Tree improvement algorithm FPgrowth* and FPmax*.Experimental...

The effective mining frequent item sets is key problem in mining maximal frequent item sets. In order to overcome insufficiency of the Apriori algorithm on the mining maximal frequent item sets,and shortcoming of FP-Tree memory structure algorithm need many times traversal. This article has introduced an array technique,reduce the FP-Tree traversal time on mining frequent item sets so that the method can be sped up. And proposes by this based on the FP-Tree improvement algorithm FPgrowth* and FPmax*.Experimental results show that an array technique introduction enhancement two algorithms effective and efficient.

有效的挖掘频繁项集是挖掘最大频繁项集的关键步骤.为了克服Apriori算法在挖掘最大频繁项集上的不足,以及FP-Tree存储结构算法多次遍历的缺点,本文引进了新的矩阵技术,减少了FP-Tree遍历次数来挖掘频繁项集,提高了挖掘频繁项集和最大频繁项集效率.并以此提出基于FP-Tree的改进算法FPgrowth*和FPmax*.最后实验结果说明,矩阵技术的引进有效的提高了频繁项集和最大频繁项集挖掘效率.

 
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