1. Course project work tasks
Clustering Methods
Course project work tasks
Pasi Fränti
Speech and Image Processing Unit School of Computing
University of Eastern Finland

2. X-means
X-means is a heuristic hierarchical method that tentatively splits every cluster and applies local k- means. Splits that provide improvement according to Bayesian information criterion are accepted.
Kd-tree structure is used to speed-up k-means.
The method is potentially faster and better than k- means but the improvements realize only with low dimensional data.

3. Affinity propagation

4. Spectral clustering

5. Cluster ensemble

6. Genetic algorithm next generation

7. K-means & Random swap for graph clustering

8. Greedy EM algorithm

9. SIPU clustering data sets www-page

10. Clustering animation of Random Swap

11. SIPU clustering data sets www-page