SOM toolbox for Matlab 5. Why? The ”SOM Toolbox” project was initialized back in 1997 because there was no such thing as a proper SOM-library for MATLAB. MATLAB is a magnificient computing environment, but the tools in its neural networks toolbox for SOM were not really up to the state-of-the-art. On the other hand, the freeware SOM program package SOM_PAK is all well and good, but it’s not nearly as flexible as the MATLAB environment. So the plan was to offer a simple, well documented MATLAB function package which is easy to use and modify in the diverse needs that different people unavoidably have. Who? Numerous people have participated in the making of SOM Toolbox. In addition to the people listed in the copyright notice, Kimmo Kiviluoto, Jukka Parviainen, Mika Pollari have participated in it, not to mention those who have contributed code, given bug reports or other feedback. The common factor for us is to have been employed in the Laboratory of Information and Computer Science in the Helsinki University of Technology.

References in zbMATH (referenced in 56 articles )

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  1. Arroyo, Ángel; Herrero, Álvaro; Tricio, Verónica; Corchado, Emilio: Analysis of meteorological conditions in Spain by means of clustering techniques (2017)
  2. Peter Wittek and Shi Gao and Ik Lim and Li Zhao: somoclu: An Efficient Parallel Library for Self-Organizing Maps (2017)
  3. Ralf Mikut, Andreas Bartschat, Wolfgang Doneit, Jorge Angel Gonzalez Ordiano, Benjamin Schott, Johannes Stegmaier, Simon Waczowicz, Markus Reischl: The MATLAB Toolbox SciXMiner: User’s Manual and Programmer’s Guide (2017) arXiv
  4. Asbeh, Nuaman; Lerner, Boaz: Learning latent variable models by pairwise cluster comparison. II: Algorithm and evaluation (2016)
  5. Izquierdo, Joaquín; Campbell, Enrique; Montalvo, Idel; Pérez-García, Rafael: Injecting problem-dependent knowledge to improve evolutionary optimization search ability (2016)
  6. Li, Qianqian; Gu, Jifa: World Expo 2010 pavilions clustering analysis based on self-organizing map (2016)
  7. Koutsovasilis, Panagiotis; Driot, Nicolas; Lu, Daxining; Schweizer, Bernhard: Quantification of sub-synchronous vibrations for turbocharger rotors with full-floating ring bearings (2015) ioport
  8. Astudillo, César A.; Oommen, B. John: Topology-oriented self-organizing maps: a survey (2014) ioport
  9. Gracia, Antonio; González, Santiago; Robles, Victor; Menasalvas, Ernestina: A methodology to compare dimensionality reduction algorithms in terms of loss of quality (2014) ioport
  10. Koc, Elcin Kartal; Iyigun, Cem: Restructuring forward step of MARS algorithm using a new knot selection procedure based on a mapping approach (2014)
  11. Koc, Elcin Kartal; Iyigun, Cem; Batmaz, İnci; Weber, Gerhard-Wilhelm: Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance (2014)
  12. Koutsovasilis, P.; Schweizer, B.: Parameter variation and data mining of oil-film bearings: a stochastic study on the Reynolds’s equation of lubrication (2014)
  13. Ortiz, A.; Gorriz, J. M.; Ramirez, J.; Salas-Gonzalez, D.: Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering (2014) ioport
  14. Vanderhaegen, Frédéric; Zieba, Stéphane: Reinforced learning systems based on merged and cumulative knowledge to predict human actions (2014) ioport
  15. Cabanes, Guénaël; Bennani, Younès; Destenay, Renaud; Hardy, André: A new topological clustering algorithm for interval data (2013) ioport
  16. Kamimura, Ryotaro: Similarity interaction in information-theoretic self-organizing maps (2013)
  17. Soulat, Laurent; Ferrand, Pascal; Moreau, Stéphane; Aubert, Stéphane; Buisson, Martin: Efficient optimisation procedure for design problems in fluid mechanics (2013)
  18. Caridakis, G.; Karpouzis, K.; Drosopoulos, A.; Kollias, S.: Non parametric, self organizing, scalable modeling of spatiotemporal inputs: the sign language paradigm (2012) ioport
  19. Kamimura, Ryotaro: Comprehensibility maximization and humanly comprehensible representations (2012)
  20. Ortiz, A.; Gorriz, J. M.; Ramirez, J.; Salas-Gonzalez, D.: Unsupervised neural techniques applied to MR brain image segmentation (2012) ioport

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