Parameterized Rough-Fuzzy Classification on a Decision Table using a Threshold-Algorithms and Implementations

Rough sets, the invention of Pawlak, find various applications in knowledge engineering, for improving the quality and accuracy, subsequently, Parameterized Rough Sets Model has come into existence. In this paper, three algorithms are developed to compute parameterized rough computing based indices of similar objects in decision table with fuzzy decision attributes using a threshold on fuzziness and these algorithms are implemented these algorithms using C.