Description: 关联规则中的频繁项集生成算法Mafia1.4版本，一个效果非常好的算法，可在linux和windows下编译运行。-association rules of frequent item sets Algorithm Mafia1.4 version, a very good effect algorithm, and the Linux compiler running under windows. Platform: |
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Author:龙行天下 |
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Description: 关联规则中的频繁项集生成算法genmax，可在linux和windows下编译运行，可能不太容易看懂。-association rules of frequent item sets genmax generation algorithm, and the Linux compiler running under windows, it may not be easy to understand. Platform: |
Size: 39444 |
Author:龙行天下 |
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Description: 一篇关于数据挖掘中关联规则的综述，希望对数据挖掘感兴趣的朋友有所帮助。-one on Data Mining Association Rules Review, and I hope to data mining interested friends help. Platform: |
Size: 1934061 |
Author:yu |
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Description: 概念格挖掘关联规则的论文及源代码，程序附在论文的最后，请注意查看，绝对有效
-concept lattice Mining Association Rules papers and source code, procedures attached to the final paper, to look and totally effective Platform: |
Size: 510090 |
Author:柳学铮 |
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Description: 在数据库中发现频繁模式和关联规则是数据挖掘领域的最基本、最重要的问题。大多数早期的研究采用了类似Apriori算法的产生候选级并测试迭代的途径代价是昂贵的，尤其是挖掘富模式和长模式时，Jiawei Han提出了一种新颖的数据结构FP_tree,及基于其上的FP_growth算法，主要用于有效的进行长模式与富模式的挖掘.本文在讨论了FP_growth算法的基础上，提出了用Visual C++实现该算法的方法，并编写了算法的程序。-found in the database model and the frequent association rules is the area of data mining the most fundamental and important issues. Most of the early studies used a similar Apriori algorithm for the selection of candidates and test-iterative way was costly, particularly mining the rich patterns and long model, Jiawei Han proposed a novel data structure FP_tree and on the basis of their FP_growth algorithm used effectively the model for long and rich patterns of excavation. This paper discussed the FP_growth algorithm on the basis of the Visual C of the algorithm, and the preparation procedure of the algorithm. Platform: |
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Author:hq |
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Description: 关联规则挖掘数据产生程序.VISUAL C++
可产生满足要求的挖掘数据.-Data Mining Association Rules have procedures. VISUAL C can be produced to meet the requirements of data mining. Platform: |
Size: 23776 |
Author:徐益军 |
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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: 1621354 |
Author:刘数位 |
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Description: 提出一种新的目标表示和定位方法,该方法是非刚体跟踪的核心技术.利用均质空间掩膜规范基于特征直方图的目标表示,该掩膜引入了适合于梯度优化的空间平滑相似函数,所以可以将目标定位问题转换为局部极大值求解问题.我们利用从Bhattacharyya系数倒出的规则作为相似度量,利用mean shift procedure完成优化求解.在给出的测试用例中, 本文方法成功解决了相机移动,阴影,以及其他的图象噪声干扰.文章对运动滤波和数据关联技术的集成也进行了讨论.-A new objective and positioning method to track non-rigid body' s core technology. Standardizing the use of homogeneous space mask the characteristics of histogram based on the objectives that the mask is suitable for the introduction of gradient optimization is similar to spatial smoothing function, Therefore, targeting the problem can be converted to solve the problem of local maxima. We poured from the rules of Bhattacharyya coefficient as similarity measure, using mean shift procedure for solving optimization. give the test cases in, the method succeeded in solving the camera Mobile, shadows, and other image noise. article on the campaign filtering and data association techniques of integration were also discussed. Platform: |
Size: 2700288 |
Author:maolei |
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Description: 一些数据挖掘算法相关,包含定义网络拓扑,有关高血压研究方面的数据,朴素贝叶斯分类,关联规则基本概念,数据挖掘算法,
决策树方法在数据挖掘中的应用,训练贝叶斯信念网络,后向传播,贝叶斯信念网络,后向传播和可解释性,多层前馈神经网络-Some relevant data mining algorithms, including the definition of network topology, the high blood pressure research data, Naive Bayesian Classifier, the basic concepts of association rules, data mining algorithms, decision tree method in data mining applications, training Bayesian belief networks, to the spread of Bayesian belief networks, to the dissemination and interpretability, multi-layer feedforward neural network Platform: |
Size: 184320 |
Author:fast man |
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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: 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: |
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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: |
Size: 198656 |
Author:wangge |
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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: 经典关联规则算法实现,采用java框架结构实现，附带实现窗口-Classical association rules algorithm, using the java framework to achieve, with the window to achieve Platform: |
Size: 34816 |
Author:hongqingting |
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Search - association rules