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Conference Papers Year : 2014

PVis - Partitions' Visualizer: extracting knowledge by visualizing a collection of partitions

Abstract

Recent advances in cluster analysis highlight the importance of finding multiple meaningful partitions and point out to the need for approaches to evaluate them. They also suggest that the evaluation should consider knowledge of a domain expert. In this paper, we present a visualization method, called PVis (Partition's Visualizer), that allows the integrated visualization of a collection of partitions. PVis allows to compare the content of a set of partitions. The comparison can be done with respect to priori knowledge provided by an expert. PVis can be useful in the discovery of relevant information to the domain experts performing cluster analysis. In order to illustrate our approach, we give an example of how to perform an exploratory analysis of collections of partitions. In order to do so, we use a well-known dataset from the Bioinformatics domain, regarding molecular classification of cancer.
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hal-00955577 , version 1 (04-03-2014)

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Katti Faceli, Tieme Sakata, Andre Carlos Ponce Ferreira de Carvalho, Marcilio de Souto. PVis - Partitions' Visualizer: extracting knowledge by visualizing a collection of partitions. IEEE IJCNN 2014, Jul 2014, Beijing, China. pp.3056-3061, ⟨10.1109/IJCNN.2014.6889672⟩. ⟨hal-00955577⟩
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