clustering
This project is a collection of clustering algorithms
K-Means
General description
This project is a Python implementation of k-means clustering algorithm for vectorized input
Requirements
You should setup the conda environment (i.e. kmeans) using the environment.yml file:
conda env create -f environment.yml
Activate conda environment:
conda activate kmeans
(Run unset PYTHONPATH on Mac OS)
Input
A list of points in an n-dimensional space.
Output
The clusters of points. By default we stores the computed clusters into a csv file: output.csv. You can specify your output filename using --output argument option.
How to run:
python -m src.run --input YOUR_DATA --clusters CLUSTERS_NO
Note that the runner expects the input dataset file to be in data folder.
Run tests
python -m pytest tests/
To deactivate the conda environment:
conda deactivate