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We focus on a questionnaire consisting of three-choice question or multiple-choice question, and propose a privacy-preserving questionnaire by non-deterministic information. Each respondent usually answers one choice from the multiple choices, and each choice is stored as a tuple in a table data. The organizer of this questionnaire analyzes the table data set, and obtains rules and the tendency. If...
This paper considers rough set-based machine learning from tables. We coped with rule generation from tables with non-deterministic information, and proposed the NIS-Apriori algorithm. After executing this algorithm, as a side effect we obtain tables causing the best criterion values of the implications and tables causing the worst criterion values of the implications. We apply this property to tables...
This paper briefly surveys rough set-based framework RNIA (Rough Non-deterministic Information Analysis), which can handle tables with non-deterministic data. Each rough set-based concept in the standard tables is redefined based on the possible world semantics. Especially, in rule generation, we reconsider the definition of rules, because the standard definition of rule generation cannot be applicable...
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