Description: 了解关联规则在数据挖掘中的应用，理解和掌握关联挖掘的经典算法Apriori算法的基本原理和执行过程并完成程序设计-Understand the association rules in data mining applications, understand and grasp the classic association mining algorithm Apriori algorithm and implementation of the basic principles of the process and complete the program design Platform: |
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Author:cdd |
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Description: apriori经典算法，主要用到数组，没有用到指针，是学习数组的好例子-classical apriori algorithm, mainly used in array pointer is not used, are a good example of the array study Platform: |
Size: 969728 |
Author:jack |
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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: |
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Author:henry |
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Description: 实现Apriori算法基本功能,获取测试数据集的关联规则-Realize the basic functions of Apriori algorithm，Access to test data sets of association rules Platform: |
Size: 209920 |
Author:张伟丰 |
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Description: 数据挖掘Apriori算法和DIC算法的C++实现。-Data mining algorithm Apriori algorithm and the DIC of the C++ to achieve. Platform: |
Size: 7168 |
Author:Xu Enliang |
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Description: Apriori算法源代码，实现了算法各个模块的全部功能，比较好用-Apriori algorithm source code of the algorithm to achieve the full functionality of each module, more use Platform: |
Size: 135168 |
Author:胡飞 |
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Description: Implementation of Apriori algorithm, using C#.
Apriori is a classic algorithm for learning association rules. Apriori is designed to operate on databases containing transactions (for example, collections of items bought by customers, or details of a website frequentation). Other algorithms are designed for finding association rules in data having no transactions (Winepi and Minepi), or having no timestamps (DNA sequencing).
Description of Apriori: http://en.wikipedia.org/wiki/Apriori_algorithm- Implementation of Apriori algorithm, using C#.
Apriori is a classic algorithm for learning association rules. Apriori is designed to operate on databases containing transactions (for example, collections of items bought by customers, or details of a website frequentation). Other algorithms are designed for finding association rules in data having no transactions (Winepi and Minepi), or having no timestamps (DNA sequencing).
Description of Apriori: http://en.wikipedia.org/wiki/Apriori_algorithm Platform: |
Size: 38912 |
Author:gabi4488 |
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Description: 数据挖掘的经典算法Apriori的实现，程序运行简单，功能满足实验要求。-Data Mining the realization of the classic Apriori algorithm, the program to run a simple functional test requirements to meet. Platform: |
Size: 1024 |
Author:日新 |
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Description: 关联规则使用外部文件测试频繁项集算法源代码，java语言-Association rules to test the use of an external file frequent itemsets algorithm source code, java language Platform: |
Size: 29696 |
Author:xinmeng |
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Description: 一种新的高效Apriori算法。提出一种使用先验算法产生频繁2项目集，并给出一种简单有效的逐步缩减交易数据库的方法，加快了频繁k项目集的验证速度。-To solve the bottleneck of the apriori algorithm,a new method to generate the 2-frequent item sets is put forword. To accelerate the verification speed of the k-frequent item sets,a simple and highly efficient method of minimizing the trade database is given. Platform: |
Size: 185344 |
Author:刘曦 |
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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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