Self- and Super-organizing Maps in R: The kohonen Package
By Ron Wehrens, Lutgarde M. C. Buydens. 2007
759 citations recorded by the source corpus.
In this age of ever-increasing data set sizes, especially in the natural sciences, visualisation becomes more and more important. Self-organizing maps have many features that make them attractive in this respect: they do not rely on distributional assumptions, can handle huge data sets with ease, and have shown their worth in a large number of applications. In this paper, we highlight the kohonen package for R, which implements self-organizing maps as well as some extensions for supervised pattern recognition and data fusion.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/d87cc62dd66e49f7285eb118ce079b990fe43c97
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Johannes W. Kruisselbrink
- Ron Wehrens
- Christoph Bergmeir
- José Manuel Benítez
- Michael Biehl
- Richard H. Scheuermann
- Ryan Remy Brinkman
- Greg Finak
In Computer Vision and Pattern Recognition
- José Manuel Benítez
- Christoph Bergmeir
- Johannes W. Kruisselbrink
- Michael Biehl
- Richard H. Scheuermann
- Ryan Remy Brinkman
- Greg Finak
- Tim R. Mosmann
In Molecular Biology
- José Manuel Benítez
- Christoph Bergmeir
- Johannes W. Kruisselbrink
- Michael Biehl
- Richard H. Scheuermann
- Ryan Remy Brinkman
- Greg Finak
- Tim R. Mosmann
Citations in the corpus
- Flexible Self-Organizing Maps in kohonen 3.0 (2018, methodology): “Already on the wish list in Wehrens and Buydens (2007), this algorithm has been now included in the kohonen package.”
- Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS (2012, methodology): “kohonen The package kohonen (Wehrens and Buydens 2007) implements a standard SOM, as well as a supervised SOM with two parallel maps, and a SOM with multiple parallel maps.”
- Stereotypic Immune System Development in Newborn Children (2018, neutral): “…2.0.5 Templ et al., 2011 https://cran.r-project.org/web/packages/ robCompositions/index.html kohonen 3.0.2 Wehrens and Buydens, 2007 https://cran.r-project.org/web/packages/kohonen /index.html vegan 2.4-6 N/A…”
- CRITICAL ASSESSMENT OF AUTOMATED FLOW CYTOMETRY DATA ANALYSIS TECHNIQUES (2013, methodology): “It includes the R package kohonen [16] which was applied to cluster three FlowCAP datasets in unsupervised mode.”