Studies on the Necessary Data Size for Rule Induction by STRIM
Studies on the Necessary Data Size for Rule Induction by STRIM
复制标题
STRIM规则归纳所需数据量的研究
DOI：
10.1007/978-3-642-41299-8_20
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Shoutarou Mizuno
中科院分区：
文献类型：
--
作者：
Y. Kato;T. Saeki;Shoutarou Mizuno
STRIM（统计测试规则归纳法）被提出作为一种从决策表中有效归纳 if-then 规则的方法，该决策表被视为从感兴趣的总体中获得的样本集。通过预先指定规则的模拟实验以及与传统方法的比较，证实了其有用性。然而，未来的研究仍有空间。需要检查的一个方面是确定通过模拟实验归纳真实规则所需的数据集的大小，因为寻找统计上显着的规则是该方法的核心。本文检验了STRIM以概率w[%]引入真实规则所需的理论必要数据集大小与规则长度的关系，并通过规则长度为2的模拟实验证实了本研究的有效性。结果为分析现实数据集提供了有用的指导。
STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by a simulation experiment specifying rules in advance, and by comparison with the conventional methods. However, there remains scope for future studies. One aspect which needs examination is determination of the size of the dataset needed for inducting true rules by simulation experiments, since finding statistically significant rules is the core of the method. This paper examines the theoretical necessary size of the dataset that STRIM needs to induct true rules with probabilityw[%] in connection with the rule length, and confirms the validity of this study by a simulation experiment at the rule length 2. The results provide useful guidelines for analyzing real-world datasets.