Description: A program to find frequent itemsets (also closed and maximal) with the eclat algorithm ,which carries out a depth first search on the subset lattice and determines the support of itemsets by intersecting transaction lists. -A program to find frequent itemsets (also c losed and maximal) with the eclat algorithm, which carries out a depth first search on the sub set lattice and determines the support of items ets by intersecting transaction lists. Platform: |
Size: 32201 |
Author:无心 |
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Description: A program to find frequent itemsets with the relim algorithm (recursive elimination), which is inspired by the FP-growth algorithm, but does its work without prefix trees or any other complicated data structures. The main strength of this algorithm is not its speed (although it is not slow, but even outperforms apriori and eclat on some data sets!), but the simplicity of its structure. Basically all the work is done in one recursive function of about 60-70 lines of code. The current version can only find free item sets. An extension to closed and maximal item sets is possible and may be available in the future.-A program to find frequent itemsets with th e relim algorithm (recursive elimination). which is inspired by the FP-growth algorithm, but does its work without prefix trees or any oth er complicated data structures. The main stren gth of this algorithm is not its speed (although it is not slow, but even outperforms apriori and eclat on some d was observed sets!) , but the simplicity of its structure. Basically all the work is done in one of recursive function about 60-70 lines of code. The current version c an only find free item sets. An extension to clos ed and maximal item sets is possible and may be av ailable in the future. Platform: |
Size: 30955 |
Author:clark |
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Description: MAFIA is a new algorithm for mining maximal frequent itemsets from a transactional database. Platform: |
Size: 733116 |
Author:鲁剑锋 |
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Description: A program to find frequent itemsets with the relim algorithm (recursive elimination), which is inspired by the FP-growth algorithm, but does its work without prefix trees or any other complicated data structures. The main strength of this algorithm is not its speed (although it is not slow, but even outperforms apriori and eclat on some data sets!), but the simplicity of its structure. Basically all the work is done in one recursive function of about 60-70 lines of code. The current version can only find free item sets. An extension to closed and maximal item sets is possible and may be available in the future.-A program to find frequent itemsets with th e relim algorithm (recursive elimination). which is inspired by the FP-growth algorithm, but does its work without prefix trees or any oth er complicated data structures. The main stren gth of this algorithm is not its speed (although it is not slow, but even outperforms apriori and eclat on some d was observed sets!) , but the simplicity of its structure. Basically all the work is done in one of recursive function about 60-70 lines of code. The current version c an only find free item sets. An extension to clos ed and maximal item sets is possible and may be av ailable in the future. Platform: |
Size: 33792 |
Author:clark |
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Description: 最大频繁项集挖掘算法。运行前需将release中的data和result数据拷贝到上一级目录下。-Maximal frequent itemsets mining algorithm. Needs to be run before the release of data and result data are copied to the directory level. Platform: |
Size: 1021952 |
Author:芳芳 |
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Description: MAFIA is a new algorithm for mining maximal frequent itemsets from a transactional database. Platform: |
Size: 733184 |
Author:鲁剑锋 |
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Description: 关联规则挖掘的研究工作主要包括：Apriori算法的扩展、数量关联规则挖掘、关联规则增量式更新、无须生成候选项目集的关联规则挖掘、最大频繁项目集挖掘、约束性关联规则挖掘以及并行及分布关联规则挖掘算法等，其中快速挖掘与更新频繁项目集是关联规则挖掘研究的重点，也是多种数据挖掘应用中的技术关键，已用于分类规则挖掘和网络入侵检测等方面的研究。研究者还对数据挖掘的理论进行了有益的探索，将概念格和粗糙集应用于关联规则挖掘中，获得了显著的效果。到目前为止，关联规则的挖掘已经取得了令人瞩目的成绩，包括：单机环境下的关联规则挖掘算法；多值属性关联规则挖掘；关联规则更新算法；基于约束条件的关联规则挖掘；关联规则并行及分布挖掘算法等。-Association rule mining research work include: Apriori algorithm for the expansion of the number of association rules mining, incremental updating of association rules, there is no need to generate candidate itemsets of association rule mining, maximal frequent itemsets mining, association rule mining binding, as well as parallel and Distribution of association rule mining algorithm, one of the rapid mining frequent itemsets and updating of association rules mining are the focus of the study, but also a variety of data mining technology in key applications, has been used in classification rules mining and network intrusion detection studies. The researchers also carried out the theory of data mining has made useful explorations, to concept lattice and rough sets in association rule mining applied to obtain significant results. So far, the mining association rules has made remarkable achievements, including: stand-alone environment for mining association rules algorithm many associatio Platform: |
Size: 2056192 |
Author:henry |
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Description: 实现最大频繁项集挖掘的功能，希望能给大家一些帮助！互相交流学习！-The achievement of maximal frequent itemsets mining functions, I hope to give you some help! Learn from each other! Platform: |
Size: 1572864 |
Author:李红霞 |
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Description: A program to find association rules and frequent item sets (also closed and maximal) with the apriori algorithm (Agrawal et al. 1993), which carries out a breadth first search on the subset lattice and determines the support of itemsets by subset tests. This is a pretty fast implementation that uses a prefix tree to organize the counters for the item sets. The census data set may be used to test the program. Platform: |
Size: 123904 |
Author:hjp |
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Description: 最大频繁模式树算法，可以自动识别集合中频繁出现的模式，在网页信息抽取中可以区分主回帖-Maximal frequent pattern tree algorithm, can automatically identify frequent patterns set in the Web information extraction can be distinguished in the main Replies Platform: |
Size: 21504 |
Author:zhaojiguang |
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Description: fcbo - 计算形式概念和最大频繁项集。这
程序计算对象属性集（形式背景）的所有形式概念的内涵，即算法计算一个布尔矩阵。-fcbo- computes formal concepts and maximal frequent itemsets. This program computes intents of all formal concepts in an object-attribute data set (a formal context), i.e. the algorithm computes all maximal submatrices of a boolean matrix which are full of 1 s. Platform: |
Size: 4096 |
Author:wangqi |
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Search - maximal frequent