| 1. | A rule induction algorithm for incomplete
不完备信息系统规则推理算法 |
| 2. | A method of rule induction based on rough set theory in inconsistent information system
基于粗糙集的不一致信息系统规则获取方法 |
| 3. | Rule induction algorithm , a mining algorithm widely used in intrusion detection fields , is researched in this thesis
本文研究了在入侵检测领域广泛应用的挖掘算法? ?规则归纳分类算法。 |
| 4. | Based on these theoretical work , we design and implement a prototype kdd system which is divided into four sections : preprocessing section , data reduction section , rule induction and decision algorithm section
在理论工作的基础上，我们设计并实现了一个基于粗集的数据约简的原型系统。 |
| 5. | Based on ripper , some modification was proposed to adapt the intrusion detection environment , resulting in the multi - greedy and coupling ( mgc ) rule induction learning algorithm
本文在ripper算法的基础上，进行了适太原理工大学硕士研究生毕业论文应入侵检测环境的改造，提出了多级贪婪祸合规则归纳算法。 |
| 6. | Motivated by this , ramesh agarwal and mahesh v . joshi presented a new framework for classification named two - phase rule induction the experiment results tell us that two - phase rule induction can get good result when classify rare class
基于此， rameshagarwal和maheshv . joshi提出了基于规则的两阶段方法去除覆盖的非目标类实例，实验结果证明两阶段方法能够很好的分类稀有类。 |
| 7. | The research work in this dissertation is based on the following observations : ( 1 ) most existing rough set methods lack of suitable means to deal with distributed data environment ; ( 2 ) since the decision support ability of decision table will be reduced in rule induction process , the obtained rules can only offer limited decision support compared with the decision table
本论文主要针对现存粗糙集方法缺乏对分布式存储数据的代价较小的有效处理机制以及在规则约简过程中决策表决策支持能力的损失等问题进行了研究工作，提出了解决方法。论文针对现存粗糙集方法缺乏对分布式存储数据的代价较小的处理机制问题，提出了元信息方法。 |
| 8. | Being of explicitness , simpleness and completeness , concept lattice has been the one focus of researchers on ai , but low performance in construction and rules induction come along with the structure . in this thesis , we consider improving the performance by simplifying the structure from the angle of classification
概念格以其知识表示的直观、简洁和完备特点而受到研究者的关注，但概念格在结构构造和规则求解方面存在低效的缺点，本文从数据分类的角度研究概念格结构的简化问题，主要讨论有确定类别属性和无确定类别属性的两类分类问题。 |
