Description: 关联规则挖掘算法FPtree的源代码，是一种不必产生候选集的关联规则挖掘算法-association rule mining algorithm FPtree of source code, is a candidate need not have a set of association rules mining algorithm Platform: |
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Author:sunqiao |
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Description: 本文根据数据挖掘中关联规则的性质以及高校成绩管理数据库的自身特点。在经典关联规则算法Apriori算法的基础上提出了一种改进的算法A++算法，并利用该算法对学生成绩管理数据库进行了关联规则挖掘，得到了隐含在数据库中的有用信息。-Based on data mining association rules in the nature of the college performance management database to its own characteristics. In the classic Apriori algorithm for association rule algorithm based on an improved algorithm A++ Algorithm, and using the algorithm of student achievement management of database for mining association rules, have been implied in the database of useful information. Platform: |
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Author:梁旭 |
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Description: 是zuojie用java实现的gep库，加上我在上面实现的关联规则挖掘。-Is zuojie realize the GEP with java database, together with the above I realize the association rule mining. Platform: |
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Author:Jacky Gao |
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Description: Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering
techniques that are frequently used in data mining have been developed in machine learning
research community. Frequent pattern and association rule mining is one of the few excep-
tions to this tradition. The introduction of this technique boosted data mining research and its
impact is tremendous. The algorithm is quite simple and easy to implement. Experimenting
with Apriori-like algorithm is the fi rst thing that data miners try to do. Platform: |
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Author:鱼彬彬 |
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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: 本文提出了基于遗传算法的关联规则的提取方法，并从编码方法、适应度函数的构造、交叉算子和变异算子的设计等方面进行了详细都讨论和分析，并结合我校的智能型学生测评系统，给出了用遗传算法进行关联规则挖掘的实例。-This paper brings forward the algorithms based on the genetic algorithms of association rules,discusses and analyses the genetic algorithms in detail from coding method,fitness function,crossover operators,selection operators,mutation operators and other aspects.Associated with the Student Evaluation System,this paper gives the algorithms and program of mining association rule based on genetic algorithms. Platform: |
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Author:yunzhang |
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Description: Data mining purpose is to find interesting patterns within great number of data. One of its functionality is association that is finding association rule which meet minimum support value (minsup) and minimum confidence (minconf). Association technique by using a minsup has been developed in many researches. Using single minimum support in data which frequency of items vary a great deal can make problems. If minsup is too high, there wouldn’t be found any rules contain rare item, if minsup is too low there would be too many rules find and some rules are meaningless.-Data mining purpose is to find interesting patterns within great number of data. One of its functionality is association that is finding association rule which meet minimum support value (minsup) and minimum confidence (minconf). Association technique by using a minsup has been developed in many researches. Using single minimum support in data which frequency of items vary a great deal can make problems. If minsup is too high, there wouldn’t be found any rules contain rare item, if minsup is too low there would be too many rules find and some rules are meaningless. Platform: |
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Author:andik |
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Description: A client server application implementing the Association Rule Mining algorithms in java. Platform: |
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Author:koldheart |
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Description: ARTool is asoftware written in Java which implements the Association Rule Mining algorithms. Platform: |
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Author:koldheart |
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Description: 关联规则隐藏技术算法的资料，厘米昂阐述了两种算法实现。-Association Rule Hiding Algorithm of data, cm Aung described two algorithms. Platform: |
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Author:ajpf |
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Description: 关联规则挖掘用以发现商品销售中的顾客购买模式。本源代码给出了关联规则挖掘算法中最经典的算法Apriori算法的实现。-Association rule mining to find merchandise sales in customer buying patterns. Source code gives the association rules mining algorithm is the most classic Apriori algorithm. Platform: |
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Author:wangge |
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Description: 关联规则挖掘的Apriori算法的，实现，希望对大家的学习有帮助。-Apriori association rule mining algorithms, to achieve, we want to help learning. Platform: |
Size: 21504 |
Author:lands |
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