Application of Rough Set-Based Information Analysis to Questionnaire Data
Naoto Yamaguchi*, Mao Wu*, Michinori Nakata**,
and Hiroshi Sakai*
*Integrated System Engineering, Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804-8550, Japan
**Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba 283-8555, Japan
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.
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