K-means we are using it when we want to group the closest data to each other.
Than we set the centroid in the center of this data and re-do this steps.
Untill there are no changes in the replacement of the centroid.
python3 sample.py
python3 sample_scratch.py
- https://developers.google.com/machine-learning/clustering/algorithm/run-algorithm
- https://realpython.com/k-means-clustering-python/
- https://medium.com/machine-learning-algorithms-from-scratch/k-means-clustering-from-scratch-in-python-1675d38eee42
- https://stanford.edu/~cpiech/cs221/handouts/kmeans.html
- https://www.saedsayad.com/clustering_kmeans.htm
- https://mmuratarat.github.io/2019-07-23/kmeans_from_scratch