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- A Study on the Risk Decision Rules Mining of IT Project Based on Rough Set 基于粗糙集的IT项目风险决策规则挖掘研究
- Decision Rules Mining 决策规则挖掘
- There are no decision rules with which to choose decision rules. 它可以告诉我们该选用哪一条规则来进行操作。
- Association rule mining is an important task of data mining. 关联规则是数据开采的重要研究内容 .
- Concerning decision table, the concept of partial granulation was introduced, and an algorithm of dynamic mining of decision rules based on partial granulation was proposed. 摘要针对决策表，引入了偏序粒的概念，提出了一种基于偏序粒的动态决策规则提取算法。
- An approach of reduction decision table is proposed to induce decision rules. 并在此基础上，给出了一种决策表的简化方法，推导出决策规则。
- At last, the authors get the decision table and distill decision rules. 最后得到决策表的简化表，并从中提取出决策规则。
- In order to improve the trustiness and accuracy of association rules mining, the association rules mining is reduced to the multi-step decision process, and an optimal strategy is proposed based on dynamic programming. 摘要为了得到准确可信任的关联规则，将关联规则的发现归纳为多阶段决策问题，利用动态规划方法对关联规则发现进行优化分析。
- By the research of discernibility matrix in rough sets, the extended class feature matrices are presented.A mining algorithm for concise decision rules based on rough set theory is proposed. 摘要研究粗糙集理论中可辨识矩阵，扩展了类别特征矩阵，提出一种基于粗糙集理论的最简决策规则算法。
- Although the values are numeric, association rules mining requires the values to be categorical. 虽然都是整型值,关联规则挖掘要求值是无条件的。
- A set of fuzzy association rules mined from the networ... 最后,文中利用遗传算法优化模糊成员函数来选择其参数。
- Finally, a new prototype system with 596 decision rules in it, based on fuzzy inference, is developed. 最后，本文发展出一个以模糊推论为基础且含596条决策规则的新原型系统。
- Authors propose association rules mining approach based on iceberg queries for analyzing the corelation between net flow and each IP address, and acquire quite good results. 作者采用基于冰山查询的关联规则挖掘方法,对网络流量与各IP之间的联系进行关联分析,取得了较好的效果。
- Decision inference of the extended decision rules was implemented using fuzzy CRI (compositional rule of inference). 用关系合成的模糊推理方法，实现了扩展决策规则集的决策推理。
- This paper firstly presents a power set-based association rules mining algorithm which uses pow er set as an association rules mining tool. 首次提出了利用幂集作为挖掘关联规则的工具,给出了基于幂集的关联规则挖掘算法。
- With the basic principle of rough set, customers dig out the decision rules they wanted. 利用粗糙集理论的基本原理,挖掘出用户需要的决策规则。
- Fpmine-SPF algorithm has a far taster speed in association rules mining than the widely used Apriori algorithm and has wonderful scalability. Fpmine-SPF算法挖掘关联规则的速度远快于较长期以来广泛使用的Apriori算法，并有相当好的可伸缩性。
- Third, we propose a new way of decision rules extracting based on the discriminated matrics. 再次，提出了一种基于可分辨矩阵的决策规则提取新方法。
- By making a survey of the theories and approaches, we proposed the iFP-Growth algorithm for the association rules mining for the web content data. 本文总结了多种从Web页面中提取半结构化数据的理论与方法，针对Web内容数据的特点，提出的增量式挖掘方法iFP-Growth，使传统的FP-Growth方法适应于动态数据环境的关联规则挖掘。
