Proceedings of the International Conference on Knowledge Discovery and Information Retrieval 2012
DOI: 10.5220/0004134300450054
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A Semi-supervised Learning Framework to Cluster Mixed Data Types

Abstract: Abstract:We propose a semi-supervised framework to handle diverse data formats or data with mixedtype attributes. Our preliminary results in clustering data with mixed numerical and categorical attributes show that the proposed semi-supervised framework gives better clustering results in the categorical domain. Thus the seeds obtained from clustering the numerical domain give an additional knowledge to the categorical clustering algorithm. Additional results show that our approach has the potential to outperfo… Show more

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