Detecting and Verifying Dissimilar Patterns in Unlabelled Data

Abstract

Clustering of unlabelled data is a difficult problem with numerous applications in various fields. When input space dimensions are many, the number of distinct patterns in the data is not known a priori, and feature scales are different, then the problem becomes much harder. In this paper we deal with such a problem. Our approach is based on an extension to… (More)

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Cite this paper

@inproceedings{Wallace2004DetectingAV, title={Detecting and Verifying Dissimilar Patterns in Unlabelled Data}, author={Manolis Wallace and Phivos Mylonas and Stefanos D. Kollias}, year={2004} }