SNOB-Clustering-Algorithm-Python-Implementation-

This repo contains the Python implementation of the Snob Algorthim presented in the paper "Wallace's Approach to Unsupervised Learning: the Snob Program". The Snob function, originally present in Matlab is implemented in Python using Oct2py.

Steps:

1. Install Octave on your system
2. Install Python Library Oct2py
3. Export Snob files to your working directory
4. Modify Clustering.m file as per your input and output file locations.

Paper Ref: https://www.researchgate.net/publication/33051996_Wallace's_Approach_to_Unsupervised_Learning_The_Snob_Program

The code is used to extract features from a dataset of customer transactions using RFM analysis and employ SNOB to group the customers based upon their transactional behavior to identify patterns that would be difficult to detect through manual inspection