Iris Hierarchical Clustering

Description

This project conducts hierarchical clustering on the Iris dataset which contains 4 dimensions/attributes and 150 samples. Each sample is labeled as one of the three type of Iris flowers.

Install

This project implemented using Python 3.7 and the following Python libraries:

• Jupyter Notebook (IPython) 4.10.0
• NumPy 1.16.4
• Pandas 0.24.0
• matplotlib 2.2.4
• scikit-learn 0.19.2
• seaborn 0.8.1

Code

The code is provided in the iris-hierarchical-clustering.ipynb notebook file. The dataset is imported using scikit Iris dataset library.

Run

In a terminal or command window, navigate to the top-level project directory iris-hierarchical-clustering/ (that contains this README) and run one of the following commands:

jupyter iris-hierarchical-clustering.ipynb

This will open the Jupyter Notebook software and project file in your browser.