4 ms·
Is there a good heuristic for picking a reasonable number of clusters automatically for an arbitrary set of vectors?
by yeldarb 4y ago
Is there a good heuristic for picking a reasonable number of clusters automatically for an arbitrary set of vectors?
- motiwari 4y agoThe elbow method is pretty common! https://en.wikipedia.org/wiki/Elbow_method_(clustering) https://en.wikipedia.org/wiki/Elbow_method_(clustering) You can also use some regularization criterion (AIC, BIC, or other)
- esalman 4y agoI usually go with Davies-Bouldin index but there are a few methods: Python/Sklearn: https://scikit-learn.org/stable/modules/clustering.html#clustering-evaluation https://scikit-learn.org/stable/modules/clustering.html#clus... R: https://cran.r-hub.io/web/packages/clusterCrit/clusterCrit.pdf https://cran.r-hub.io/web/packages/clusterCrit/clusterCrit.p...
- syntaxfree 4y agoYou could always try to use a density based clusterer like DBSCAN, HDBSCAN or OPTICS to determine a likely number of clusters.