Application of Rough Set-Based Information Analysis to Questionnaire Data

抄録

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.