Application of Rough Set-Based Information Analysis to Questionnaire Data

被引：2
|
作者：
Yamaguchi, Naoto [1 ]
Wu, Mao [1 ]
Nakata, Michinori [2 ]
Sakai, Hiroshi [1 ]
机构：
[1] Kyushu Inst Technol, Grad Sch Engn, Integrated Syst Engn, Kitakyushu, Fukuoka 8048550, Japan
[2] Josai Int Univ, Fac Management & Informat Sci, Togane, Chiba 2838555, Japan
来源：
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2014年 / 18卷 / 06期
基金：
日本学术振兴会;
关键词：
rough sets; table data analysis; missing values; questionnaire; question-answering;
D O I：
10.20965/jaciii.2014.p0953
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article reports an application of Rough Nondeterministic Information Analysis (RNIA) to two data sets. One is the Mushroom data set in the UCI machine leaning repository, and the other is a student questionnaire data set. Even though these data sets include many missing values, we obtained some interesting rules by using our getRNIA software tool. This software is powered by the NIS-Apriori algorithm, and we apply rule generation and question-answering functionalities to data sets with nondeterministic values.
引用
收藏
页码：953 / 961
页数：9
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