Developing a Rule Evaluation Support Method Based on Objective Indices
Developing a Rule Evaluation Support Method Based on Objective Indices
复制标题
DOI：
10.1007/11795131_66
复制
发表时间：
2006-07
期刊：
影响因子：
--
通讯作者：
H. Abe;S. Tsumoto;M. Ohsaki;Takahira Yamaguchi
中科院分区：
文献类型：
--
作者：
H. Abe;S. Tsumoto;M. Ohsaki;Takahira Yamaguchi
数据挖掘后处理是数据挖掘过程中的关键环节之一，本文对一种新的规则评价支持方法的学习算法进行了评价。对于人类专家来说，很难从一个带有噪声的大型数据集中完全评估数千条规则。为了降低规则评价任务的成本，我们开发了基于规则评价模型的规则评价支持方法，该模型是由客观指标和人类专家对每条规则的评价组成的数据集学习而来的。为了增强规则评价模型的适应性，我们引入了一个建设性的元学习系统来选择合适的学习算法来构建规则评价模型。然后，对8个UCI数据集的脑膜炎数据挖掘结果、肝炎数据挖掘结果和规则集进行了案例研究。
In this paper, we present evaluations of learning algorithms for a novel rule evaluation support method in data mining post-processing, which is one of the key processes in a data mining process. It is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which are learned from a dataset consisted of objective indices and evaluations of a human expert for each rule. To enhance adaptability of rule evaluation models, we introduced a constructive meta-learning system to choose proper learning algorithms for constructing them. Then, we have done a case study on the meningitis data mining result, the hepatitis data mining results and rule sets from the eight UCI datasets.