Deploy the association rule mining flow as a DB2 stored procedure.
将关联规则挖掘流部署为DB 2存储过程。
Create a Cognos report using results from dynamic association rule mining.
使用来自动态关联规则挖掘的结果创建一个Cognos报告。
This paper introduces an ILP Method Applied in Spatial Association Rule Mining.
文章介绍了应用于空间关联规则挖掘的ILP方法。
Association rule mining requires the user to state a minimal support and confidence.
关联规则挖掘要求用户要能说明最少support和confidence。
All association rules can be derived by covering the smallest association rule set.
所有的关联规则都可以通过覆盖最小的关联规则集得到。
Aim To put forward association rule mining algorithm based on relation algebra theory.
目的提出基于关系代数理论的关联规则挖掘算法。
This paper proposes a Chinese conception sets-generating algorithm based on association rule.
本文提出了一种基于关联规则的中文概念集生成算法。
First, learn about the task of association rule mining and how to achieve it in InfoSphere Warehouse.
首先，我们先来了解关联规则挖掘的任务以及如何在InfoSphere Warehouse内实现此任务。
To create the association rule mining model and extract the rules to a database table, do the following
要创建关联规则挖掘模型并将这些规则提取到数据库表，可以执行如下操作
Association rule mining which is a method of data mining reveals the latent information and knowledge.
作为一种数据挖掘的方法，关联规则揭示了数据中隐藏的信息和知识。
In this thesis, the thorough study of time serial model, classification rule and association rule is made.
本文对时间序列模式、分类规则和关联规则挖掘的方法进行了深入的研究。
Note, now the association rule mining flow is executing and returning the extracted rules to Framework Manager.
现在，关联规则挖掘流被执行并将所提取的规则返回给Framework Manager。
Association rule is a simple statement about the cooccurrence probability of some certain events in database.
关联规则是数据库中某些特定事件一起发生的概率的简单陈述。
Subsequently, the association rule discovery algorithm is employed to discover the sequence association rules.
最后应用关联规则发现算法进而发现序列关联规则。
Second, we realize application and prediction by association rule mining in the audit department of tax system.
利用关联规则算法实现了在税务稽查部门进行预测的方法。
Feature association rule mining is filtering and finding characteristic patterns between object and background.
特征关联就是从复杂背景中筛选与发现目标特征，揭示目标与背景之间的特征模式。
The approach of using association rule algorithm to determine the optimization value is presented in this paper.
论文提出了基于关联规则算法的目标值确定的设计思路。
In this article you learned about association rule mining and how to find association rules with InfoSphere Warehouse.
在本文中，您了解了关联规则挖掘及如何用InfoSphere Warehouse获得关联规则的有关内容。
You can use the results from association rule mining to set up bundles of packages that customers tend to buy together.
您可以使用关联规则中规则进行挖掘，然后设置用户有意要一起购买的捆绑包。
Association rule mining is invoked by calling a stored procedure as all other mining operations in InfoSphere Warehouse.
对关联规则挖掘的调用是通过调用一个存储过程完成的，与InfoSphere Warehouse内的所有其他挖掘操作无异。
Association rule learning searches for relationships between data objects to make predictions, position products, and so on.
关联性规则学习(Association rule learning)搜寻数据对象之间的关系，以做出预言、定位产品，等等。
The paper presents the application of association rule mining in analyzing techniques and tactics of table tennis match.
介绍关联规则挖掘技术在乒乓球比赛技战术分析中的应用。
Association rule is a method of data mining, whose typical application is the analysis of shopping basket in supermarket.
关联规则是数据挖掘的一种方法，它的最典型的应用是超市的购物篮分析。
While they are commonsense, association rule mining can find many other interesting interactions, such as' beer and diaper '.
有趣的是，关联规则挖掘能找到，像“啤酒与尿不湿”被同时销售，这种非常识性知识。
Major methods to distill network intrusion mode are class algorithm, association rule algorithm and frequent episodes algorithm.
提取网络入侵模式所用的主要有分类算法、关联规则算法和序列规则算法等。
It analyzes the express method of affair and association rule in the binary system sequences set and complexity in space and time.
分析了事务与关联规则在二进制序列集中的表示方法及其在空间、时间上的复杂度。
Association rule mining may help making many business decisions such as catalog design, cross-marketing, and loss-leader analysis.
关联规则挖掘可以帮助许多商务决策的制定，如分类设计、交叉购物和贱卖分析。
The system gives two kinds of recommendation algorithms based on association rule mining and user's transaction pattern clustering.
本系统给出了基于关联规则挖掘和基于用户事务模式聚类两种推荐算法。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
应用推荐