The output of association mining is a set of rules of the form.
关联挖掘的输出是一组采用以下形式的规则。
In this paper, we connected fuzzy set theory with association mining, and proposed a fuzzy association data mining arithmetic.
本文把模糊集理论和传统的关联挖掘结合在一起，提出了一种模糊关联数据挖掘算法。
Association rule mining is a highly interactive task, and users usually have to try many different parameter Settings to achieve the desired result.
关联规则挖掘是一项高度交互的任务，用户通常需要尝试多种参数设置才能达到理想的结果。
Association rules are one of the techniques used in data mining, and particularly useful with e-commerce transactional information.
关联规则是在数据挖掘中所使用的一种技术，并对电子商务事务信息非常有用。
You can express each rule found in the data mining as a merchandising association.
您可以将在数据挖掘中发现的每条规则表示成商品销售关联。
Mining association rules require two pieces of data, the transaction and what was bought in that transaction.
挖掘关联规则需要两方面的数据，事务及该事务中所包含的信息。
You have learned that data mining with association rules is a useful way to identify related items in your customers' shopping carts.
您已经学习到了使用关联规则的数据挖掘是识别出在顾客购物车中的相关条目的有用的方式。
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。
In the following example, see how to create the mining flow, creating the association model and extracting the rules from it.
下面的示例显示了如何创建挖掘流程，同时创建关联模型并从中提取规则。
Within the report, you can enter parameters to change the mining parameters. In this example, a revenue-per-product list allows you to drill-through to association rules for the specific products.
在本示例中，有一个针对每个产品的收入列表，借助它就能够穿透钻取特定产品的关联规则。
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。
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
Market basket analysis and association rule mining.
市场购物篮分析及关联规则挖掘。
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。
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。
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。
There are many application scenarios in which association rule mining is used.
关联规则挖掘的应用场景很多。
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。
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。
Bruce Watzman, senior vice President for regulatory affairs at the National Mining Association, an industry group, urged the committee not to impose increased regulation.
布鲁斯·瓦茨曼，作为行业组织全国矿业协会监管事务的高级副总裁，敦促委员会不要强行增加监管。
The single minimum support degree is used in the existing association rules mining methods mostly.
现有的关联规则挖掘方法中，大多采用单一的最小支持度。
Secondly, it analyzed association rule and sequence mode used in the process of data mining and compared the main algorithms of association rule and sequence mode.
其次，分析了数据挖掘中所使用的关联规则和序列模式，对关联规则和序列模式的各种挖掘算法进行了比较。
Mining association rules is a major aspect of data mining research.
挖掘关联规则是数据挖掘研究的一个重要方面。
Based on data-distort method, we propose privacy preserving association rules mining algorithm IFB-PPARM using efficient data structure namely inverted file.
基于数据变换法，提出使用高效数据结构即倒排文件的隐私保护关联规则挖掘算法ifb - PPARM。
Mining quantitative association rules is an important task of data mining.
量化关联规则的挖掘是数据挖掘的一项重要任务。
Mining association rules is a major aspect of data mining research, and maintaining discovered association rules is of equal importance.
挖掘关联规则是数据挖掘研究的一个重要方面，而维护已发现的关联规则同样是重要的。
Mining association rules is a major aspect of data mining research, and maintaining discovered association rules is of equal importance.
挖掘关联规则是数据挖掘研究的一个重要方面，而维护已发现的关联规则同样是重要的。
应用推荐