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» Self-organizing maps and symbolic data
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ESANN
2004
13 years 9 months ago
Clustering functional data with the SOM algorithm
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Fabrice Rossi, Brieuc Conan-Guez, Aïcha El Go...
ICDM
2003
IEEE
101views Data Mining» more  ICDM 2003»
14 years 1 months ago
Interactive Visualization and Navigation in Large Data Collections using the Hyperbolic Space
We propose the combination of two recently introduced methods for the interactive visual data mining of large collections of data. Both, Hyperbolic Multi-Dimensional Scaling (HMDS...
Jörg A. Walter, Jörg Ontrup, Daniel Wess...
BMCBI
2007
152views more  BMCBI 2007»
13 years 8 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
IDEAL
2005
Springer
14 years 1 months ago
Recursive Self-organizing Map as a Contractive Iterative Function System
Recently, there has been a considerable research activity in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, the ...
Peter Tiño, Igor Farkas, Jort van Mourik
NN
2006
Springer
113views Neural Networks» more  NN 2006»
13 years 7 months ago
Large-scale data exploration with the hierarchically growing hyperbolic SOM
We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
Jörg Ontrup, Helge Ritter