Comparative Study and Analysis of Wholesale Customer's Dataset Using Association Rule Mining

Vijayakumar M
2018 International Journal for Research in Applied Science and Engineering Technology  
Association Rule Mining (ARM) has always been the area of interest for many researchers for a long time and continues to be the same. It is one of the important tasks of the data mining concept. It aims at discovering relationships among various items in the database. The datamining is the computing process of discovering patterns in large datasets. It is based on complex algorithms that allow segmentation of data to identify pattern and trends, detect anomalies, and predict the probability of
more » ... arious situational outcomes. The Data mining trends includes: Distributed Data Mining (DDM), Multimedia Data Mining, Spatial and Geographic Data Mining, Time series and sequence data mining. This paper is based on Association rule mining and its methodology. The main objective of this paper is to present a review on the basic concepts of ARM technique and its algorithms. In this paper, the association rule mining algorithms namely Apriori, Predictive Apriori and Filtered Associator is being implemented in the Whole sale customer's dataset and the performance of these algorithms are compared and analyzed deeply.
doi:10.22214/ijraset.2018.1270 fatcat:73as2pvgcjftdp3jl7flwtx7ye