A simple k-means clustering implementation in Clojure. I needed clustering to find "concepts" in a clojure NLP library I'm working on and figured this component is reusable enough.
As a note, because clusters are defined as the average of their elements if a cluster ends up empty I let it stay that way. Actually it gets removed and added as an empty cluster on termination.
See sample.clj for sample usage.
Inputs to k-means are:
- A seq of elements to cluster
- A vector distance meansure
- A vectorizer for elements
- The number of clusters desired
- The maximum number of iterations
Copyright © 2014 Cody Rioux
Distributed under the Eclipse Public License either version 1.0 or (at your option) any later version.