The Completeness of NIS-Apriori Algorithm and a Software Tool GetRNIA
Hiroshi Sakai, Mao Liang Wu · 2014
Rough set-based rule generation in tables with uncertainties, especially non-deterministic information and missing values, is investigated. The possible world semantics is employed, and both certain rules and possible rules are defined. Even though these definitions cause the computational problem, it is solved by using rough set-based concepts, and NIS-Apriori algorithm is proposed as the core algorithm of rule generation. In this paper, the soundness and the completeness of NIS-Apriori algorithm is newly proved. Furthermore, a data mining web software getRNIA powered by NIS-Apriori is presented. We can easily access getRNIA software tool by searching with the keyword 'getrnia'.