Description: Apriori是数据挖掘中关联规则的经典算法，此源码是其Java实现。包内还有实例用的数据库-Data Mining Association Rules classic algorithms, this source is Java. There are examples of packages within a database Platform: |
Size: 174648 |
Author:Owen |
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Description: 一个用Apriori算法实现的数据挖掘关联规则程序-An implementation of Association Rules Data Mining using Apriori Algorithm Platform: |
Size: 84992 |
Author:潘文斌 |
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Description: apriori java 实现 * A program to find association rules with the apriori algorithm (Agrawal et al. 1993).<br> * Other than the standard apriori algorithm, this program enable to find<br> * apriori all relation.-algorithm to achieve* A program to find association rules with the algorithm algorithm (Agrawal et al. 1993). Lt; Brgt;* Other than the standard algorithm algorithm, this program to enable findlt; Brgt;* Algorithm all relation. Platform: |
Size: 5120 |
Author:石中超 |
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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: |
Size: 10240 |
Author:hq |
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Description: Apriori是数据挖掘中关联规则的经典算法，此源码是其Java实现。包内还有实例用的数据库-Data Mining Association Rules classic algorithms, this source is Java. There are examples of packages within a database Platform: |
Size: 174080 |
Author:Owen |
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Description: Apriori算法是发现关联规则领域的经典算法。该算法将发现关联规则的过程分为两个步骤：第一步通过迭代，检索出事务数据库中的所有频繁项集，即支持度不低于用户设定的阈值的项集；第二步利用频繁项集构造出满足用户最小信任度的规则-Apriori association rules algorithm is found in the field of classical algorithms. The algorithm will find the process of association rules is divided into two steps: first, through iteration, retrieve a transaction database of all the frequent itemsets, that is, support for no less than user-set threshold itemset the second step use of frequent itemsets constructed to meet the users trust in the rules of the smallest Platform: |
Size: 11264 |
Author:hey |
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Description: 数据挖掘中并行关联规则中经典Apriori算法的Java源代码实现。-Parallel data mining association rules in the classical Apriori algorithm realize the Java source code. Platform: |
Size: 4096 |
Author:张国祥 |
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Description: 用java实现数据挖掘关联规则经典算法Apriori算法-Java data mining using association rules to achieve the classic algorithm Apriori algorithm Platform: |
Size: 742400 |
Author:任修凯 |
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Description: 数据挖掘关联规则算法：Apriori算法源代码，采用JAVA语言实现-Data mining algorithm of association rules: Apriori algorithm source code, the use of JAVA language Platform: |
Size: 9216 |
Author:liuchunju |
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Description: Apriori算法的核心实现类先计算频繁项集，计算出支持度，置信度，找出关联规则-Apriori algorithm for computing the core of the implementation class first frequent item sets, calculate the support, confidence, find the association rules Platform: |
Size: 1024 |
Author:马玉洁 |
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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: 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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Description: apriori in java to identify frequent item sets. It proceeds by identifying the frequent individual items in the and extending them to larger item sets while the items satisfy the minimum support requirement (frequency of items in the ). The frequent item sets determined by Apriori are then used to determine association rules.-apriori in java to identify frequent item sets. It proceeds by identifying the frequent individual items in the and extending them to larger item sets while the items satisfy the minimum support requirement (frequency of items in the ). The frequent item sets determined by Apriori are then used to determine association rules. Platform: |
Size: 175104 |
Author:Wahyu |
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