Market basket analysis for improving the effectiveness of marketing and sales using Apriori, FP Growth and Eclat Algorithm

Abstract

Data mining approach with the help of best frequent pattern extracting algorithm can have a big impact in the field of marketing and sales. Frequent pattern mining is a widely researched field in data mining because of its importance in many real life applications. In this thesis, we used the three most popular algorithms in frequent pattern mining for market basket analysis – FP Growth, Apriori, and Eclat. The design and implementation of these three pattern mining algorithms were discussed in detail. All the three algorithms gave consistent output. We did performance comparison and analysis of these algorithms using three different datasets. Recommendations are provided to suggest the best algorithm to use in different contexts.