Description: 本程序是数据挖掘中的关联规则模型中著名的Aprior算法的VC实现程序，可用于知识发现、数据挖掘、人工智能、模式识别等领域（请先解压文件）-The code is the VC implementation of the well-known Aprior algorithm in Association Rule Model of Data Mining field, can be used in Knowledge Discovery, Data Mining, AI, Pattern Recognition and so on.(Please unzip the file first) Platform: |
Size: 73442 |
Author:杨永刚 |
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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: |
Size: 21150 |
Author:sunqiao |
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Description: 用MATLAB和VC实现关联规则挖掘的一个样例，有原码-using MATLAB and VC Mining Association Rules an example, the original code Platform: |
Size: 1620992 |
Author: |
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Description: IBM Quest Market-Basket Synthetic Data Generator是做关联规则挖掘多用的一种人工数据合成工具，这方面论文的实验数据大多是用它生成的数据。-IBM Quest Market-Basket Synthetic Data Generator for mining association rules is to do a manual multi-purpose data integration tools, this paper experimental data are data generated using it. Platform: |
Size: 17408 |
Author:熊宝强 |
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Description: matlab 关于association rule 的自己写的函数，有3个文件,
association.m：h = association(m, i, j)
i=>j, m是数据，h是support和confidence，该函数只适用于单个数据
ass_item: h=ass_itset(m, a, b)
同上，但是可用于多个数据（m为数组）
assrule: h = assrule(m, threshold1, threshold2)
该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence-matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data
ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix)
assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence Platform: |
Size: 1024 |
Author:张天为 |
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Description: 关联规则是数据挖掘的重要模式之一，有着极其重要的应用价值。本文根据关联规则挖掘的要求与特点，结合遗传算法的思想，提出了一个基于遗传算法的关联规则挖掘方法，并通过实例分析，说明是一种具有实用价值的方法。-Data mining association rules is one important model, has an extremely important value. Based on association rule mining requirements and features, combined with the idea of genetic algorithm, genetic algorithm is proposed based on association rule mining method, and through case studies, describes a method of practical value. Platform: |
Size: 467968 |
Author:张广明 |
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Description: 朴素贝叶斯分类是一种简单而高效的分类模型，然而条件独立性假设在现实中很少出，致使其性能有所下降。通过引入关联规则，从两方面来改善朴素贝叶斯分类的性能。一方面，通过对关联规则的挖掘，发现条件属性之间的关联关系，并且利用这种关联关系弱化朴素贝叶斯的独立性假设；另一方面，通过关联规则的置信度，给朴素贝叶斯加权。 -Naive Bayesian classifier is a simple and efficient classification model, the conditional independence assumption, however, rarely in the real world, resulting in decreased performance. Through the introduction of association rules, two ways to improve the performance of naive Bayesian classifier. On the one hand, by association rule mining, found the association between condition attributes and use this association weakened Bayesian independence assumption the other hand, by association rule confidence, to the simple Bayesian Alaska right. Platform: |
Size: 1310720 |
Author:张广明 |
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Description: 本文提出来一种基于关联规则挖掘的二进制粒子群优化算法（BPSO），该算法与apriori算法不同，在从交易数据集中提取关联规则的过程中不需要给定支持度与置信度的阈值。-In this paper, we developed a binary particle swarm optimization (BPSO) based association rule miner.
Our BPSO based association rule miner generates the association rules from the transactional database by
formulating a combinatorial global optimization problem, without specifying the minimum support and
minimum confi dence unlike the a priori algorithm. Platform: |
Size: 211968 |
Author:xiaowei |
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Search - association rule