Using the training data, it explains the method of mining classification rules, and abecedarian experiment results validate its effectiveness.
通过训练数据的分析阐述了分类规则挖掘的方法，初步的实验结果验证了该方法的有效性。
Genetic Programming is applied to mining classification rules, it can effectively solve multiclass classification by several two-class classifiers using structural hierarchy.
将遗传程序设计方法应用到分类规则的挖掘上，利用具有分层结构的两类别分类问题的分类器解决多类别的分类问题。
In order to improve the classification quality of decision system, a strategy of data mining classification rules based on rough approaching approximation measurement in data ware is proposed.
为了提高决策系统的分类质量，探讨了一种在数据仓库中基于粗糙逼近近似度量的挖掘分类规则策略。
Then the decision tree and class association rules mining are used on the video attribute database to extract a decision tree classification rule set and a class association rule set respectively.
然后分别使用决策树、分类关联规则等技术对视频属性数据库进行数据挖掘，提取出决策树分类规则集和分类关联规则集；
Experiment shows that the classification rule mining method using hybrid genetic algorithms can find a set of the succinct, accurate and comprehensible classification rules.
实验表明，基于混合遗传算法的分类规则挖掘方法能够从数据集中发现一个简洁、准确、易理解的规则集。
Classification is an important task in data mining field, how to discover the intelligible and interesting classification rules is one of the main problems facing data mining.
分类是数据挖掘的一项重要任务，如何发现可理解的、令人感兴趣的分类规则是数据挖掘面临的一个主要问题。
Then the method of synchronous amalgamating is chosen to implement the mining of classification rules from multiple data sources.
最后，选择规则的同步融合策略实现多数据源中的分类规则挖掘。
Data mining is an important problem in KDD, and Rough set as a theory of set with fuzzy boundary is widely applied to infer classification rules from decision system.
数据挖掘是知识发现领域的一个重要问题，粗糙集理论是一种具有模糊边界的数据挖掘方法，它被广泛应用于决策系统的分类规则提取中。
It also discusses some techniques of data mining such as mining association rules, mining sequential patterns and data classification.
对常用于入侵检测系统中的数据挖掘技术如关联规则，序列分析，分类分析等进行了分析。
Classification rules discovery is a procedure to construct a classifier through studying the training dataset. It is a very important part of data Mining and Knowledge discovery.
分类规则发现则是通过对训练样本数据集的学习构造分类规则的过程，是数据挖掘、知识发现的一个重要方面。
It includes lots of measures such as association rules mining, classification and prediction, clustering analysis and evolvement analysis.
它包含关联规则挖掘、预测、分类、聚类、演化分析等多种技术手段。
The tasks of data mining include association rules analysis, time series module, cluster analysis, classification and predication and so on.
数据挖掘的任务有关联分析、时序模式、聚类、分类与预测等。
The tasks of data mining include association rules analysis, time series module, cluster analysis, classification and predication and so on.
数据挖掘的任务有关联分析、时序模式、聚类、分类与预测等。
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