Abstract
Robust mixture models approaches, which use non-normal distributions have recently been upgraded to accommodate data with fixed bounds. In this article we propose a new method based on uniform distributions and Cross- Entropy Clustering (CEC). We combine a simple density model with a clustering method which allows to treat groups separately and estimate parameters in each cluster individually. Consequently, we introduce an effective clustering algorithm which deals with non-normal data.
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Brzeski, M., & Spurek, P. (2016). Uniform cross-entropy clustering. Schedae Informaticae, 25, 117–126. https://doi.org/10.4467/20838476SI.16.009.6190
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