Introduction to Cross-Entropy Clustering The R Package CEC

2015/08/19 by Jacek Tabor, Tabor, Jacek, Przemysław Spurek +7
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #cs.LG #stat.ME #stat.ML

paper · pdf · doi:10.48550/arxiv.1508.04559

arxiv created 2015/08/19 · arxiv updated 2015/08/20

Abstract

The R Package CEC performs clustering based on the cross-entropy clustering (CEC) method, which was recently developed with the use of information theory. The main advantage of CEC is that it combines the speed and simplicity of k-means with the ability to use various Gaussian mixture models and reduce unnecessary clusters. In this work we present a practical tutorial to CEC based on the R Package CEC. Functions are provided to encompass the whole process of clustering.

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