Mixtures of Rectangles: Interpretable Soft Clustering
Dan Pelleg, Andrew Moore · 2001
To be eective, data-mining has to conclude with a succinct description of the data. To this end, we explore a clustering technique that nds dense regions in data. By constraining our model in a speci c way, we are able to represent the interesting regions as an intersection of intervals. This has the advantage of being easily read and understood by humans.