Clustering using kernel entropy principal component analysis and variable kernel estimator
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DOI: 10.11591/ijece.v11i3.pp2109-2119
Abstract: Clustering as unsupervised learning method is the mission of dividing data objects into clusters with common characteristics. In the present paper, we introduce an enhanced technique of the existing EPCA data transformation method. Incorporating the… read more here.
Keywords: kernel entropy; entropy; using kernel; entropy principal ... See more keywords