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INFOVIS
2005
IEEE
13 years 12 months ago
Multivariate Glyphs for Multi-Object Clusters
Aggregating items can simplify the display of huge quantities of data values at the cost of losing information about the attribute values of the individual items. We propose a dis...
Eleanor Boyle Chlan, Penny Rheingans
ICDAR
2003
IEEE
13 years 11 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 9 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
GECCO
2010
Springer
338views Optimization» more  GECCO 2010»
13 years 4 months ago
Multiobjective evolutionary community detection for dynamic networks
A multiobjective genetic algorithm for detecting communities in dynamic networks, i.e., networks that evolve over time, is proposed. The approach leverages on the concept of evolu...
Francesco Folino, Clara Pizzuti
ASUNAM
2010
IEEE
13 years 5 months ago
A Multiobjective and Evolutionary Clustering Method for Dynamic Networks
—The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. Previous evolutionary based clustering methods try to maxi...
Francesco Folino, Clara Pizzuti