TY - JFULL AU - Sudhir Jagtap and Kodge B. G. and Shinde G. N. and Devshette P. M PY - 2012/2/ TI - Role of Association Rule Mining in Numerical Data Analysis T2 - International Journal of Computer and Information Engineering SP - 121 EP - 125 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/9376 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 61, 2012 N2 - Numerical analysis naturally finds applications in all fields of engineering and the physical sciences, but in the 21st century, the life sciences and even the arts have adopted elements of scientific computations. The numerical data analysis became key process in research and development of all the fields [6]. In this paper we have made an attempt to analyze the specified numerical patterns with reference to the association rule mining techniques with minimum confidence and minimum support mining criteria. The extracted rules and analyzed results are graphically demonstrated. Association rules are a simple but very useful form of data mining that describe the probabilistic co-occurrence of certain events within a database [7]. They were originally designed to analyze market-basket data, in which the likelihood of items being purchased together within the same transactions are analyzed. ER -