Data mining approach based on clustering and association rules applicable to different fields
Imane Belabed, Mohammed Talibi Alaoui, Youssef Talibi Alaoui, Abdelmajid Belabed · 2018
Data mining techniques are useful to raise a significant and usable knowledge that can be applied in many areas. In this paper, an approach for extracting knowledge is proposed. Initially the variables are clustered in order to decrease the number of variables, and then association rules are used between the target variables and the previously established groups of variables. The method is applicable for both qualitative and quantitative variables. In this work, we will also compare the application of this approach in different domains.