Market basket Analysis using Associate rule mining.

Association Rule Mining is used when you want to find an association between different objects in a set, find frequent patterns in a transaction database, relational databases or any other information repository. The applications of Association Rule Mining are found in Marketing, Basket Data Analysis (or Market Basket Analysis) in retailing, clustering and classification. It can tell you what items do customers frequently buy together by generating a set of rules called Association Rules. In simple words, it gives you output as rules in form if this then that. Clients can use those rules for numerous marketing strategies

Run Locally

You can download the source code and run it in Google Colab or Jupyter Notebook.

Project Report and Dataset

The dataset which we used for Model application. The dataset includes the transaction of various purschased made from supermarkets around the world, with timestamp and their locations. checkout the dataset here:

Dataset

Here is the final report of the project, which includes the explanation to every algorithm used along with end results.

Read Report

FAQ

What Asscociation Rule Mining Algorithms were used?

Apriori and Fp-Growth