Data Mining

The primary theories that apply in fuzzy modelling are the fuzzy set theory and fuzzy logic. Fuzzy modelling facilitates the transformation of a linguistic description to an algorithm with practical results. The variables in the given admission data represent fuzzy subsets of the entire data set. For this case, ranking will not be an important consideration. The K-means algorithm will be used to group data but the problem will be finding the optimal centers of clusters and so fuzzy logic will be introduced to established the optimal centers of the clusters. By clustering, it will be easier to identify the set that the object/ data belongs (Afzali, & Mohammadi 2017). Since there is no prior knowledge of elements’ clusters, similarities will be evaluated based on the attribute values that best describe the data. The fuzzy logic will then form the variables that emerge from the data relationship.

                                                                         Reference

Afzali, G. A., & Mohammadi, S. (2017). Privacy preserving big data mining: association rule hiding using fuzzy logic approach. IET Information Security, 12(1), 15-24.