Modifying the Scale-free Clustering Method

Abstract

The aim of this study is to computationally classify, without supervision, the data points of a dataset containing real-life measurements pre-classified into two classes. The classification is done using two methods: the k-means method as a reference, and a modified version of previously presented method using a minimum spanning tree with a scale-free… (More)
DOI: 10.1109/CIMCA.2005.1631514

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