Unsupervied learning algorithms have been used to classify various customers of a company into clusters.
The dataset used is from UCI ML repository
Attribute Information:
- FRESH: annual spending (m.u.) on fresh products (Continuous);
- MILK: annual spending (m.u.) on milk products (Continuous);
- GROCERY: annual spending (m.u.)on grocery products (Continuous);
- FROZEN: annual spending (m.u.)on frozen products (Continuous)
- DETERGENTS_PAPER: annual spending (m.u.) on detergents and paper products (Continuous)
- DELICATESSEN: annual spending (m.u.)on and delicatessen products (Continuous);
- CHANNEL: customers’ Channel - Horeca (Hotel/Restaurant/Café) or Retail channel (Nominal)
- REGION: customers’ Region – Lisnon, Oporto or Other (Nominal)
Aditional information about the dataset can be found on the link above.
This project uses the following software and Python libraries:
- [Python 2.7]
- [NumPy]
- [pandas]
- [scikit-learn]
- [matplotlib]
You will also need to have software installed to run and execute a [Jupyter Notebook]