A basic implementation of an unsupervised K-means clustering algorithm. Can be used for customer segmentation, clustering different types of data, etc.
Used the classic iris dataset to cluster data points into 3 groups.
The implementation is run from the
if __name__ == '__main__':"block.
This implementation was written quickly for an assignment, so some legibility was sacrificed for speed. Having said that, it's relatively clean code for a quick implementation.
Note: numpy is requried.