K-means clustering: for each point, put the point in the cluster to whose centroid it is closest, recompute the cluster centroids, repeat loop (until there is no change in clusters between two consecutive iterations).
Hierarchical clustering methods: divisive (bisecting k-means) and agglomerative. Buckshot clustering: combines HAC and K-Means clustering.
Clustering on text: use LSI to reduce dimensions before clusterings.
Hierarchical clustering methods: divisive (bisecting k-means) and agglomerative. Buckshot clustering: combines HAC and K-Means clustering.
Clustering on text: use LSI to reduce dimensions before clusterings.
-- Shu
