Data mining algorithm based on Renyi fuzzy association rule: an application for the selection of suitable course

Data mining has been used to discover patterns in the data. It is a knowledge discovery technique to analyze hidden pattern and information from the available database. Due to uncertainty, fuzzy-based data mining techniques have been incorporated for decision-making. Fuzzy based data mining techniques model incomplete information and relations effectively in situations where lack of reasoning is given. A new fuzzy data mining algorithm has been proposed that helps in decision-making under uncertain conditions. The demonstration of the algorithm has been supported by means of a case study for the selection of suitable careers after studies. In the case study, data of 60 students studying in 4 different universities, pursuing 3 different courses have been taken. The decision making for the preparatory classes such as, further studies (F-S) or for job-oriented (JO) or coaching has been done by using the proposed method. From the results, it is concluded that student studying in the university U2 pursuing course C2 will take preparatory classes for job oriented course.