A self-organizing map (SOM) or self-organizing feature map (SOFM) is an unsupervised machine learning technique used to produce a low-dimensional (typically...

be self-organizing. Paul Krugman has written on the role that market self-organization plays in the business cycle in his book The Self Organizing Economy...

In artificial neural networks, a hybrid Kohonen self-organizing map is a type of self-organizing map (SOM) named for the Finnish professor Teuvo Kohonen...

A growing self-organizing map (GSOM) is a growing variant of a self-organizing map (SOM). The GSOM was developed to address the issue of identifying a...

Generative topographic map (GTM) is a machine learning method that is a probabilistic counterpart of the self-organizing map (SOM), is probably convergent...

theorem Discriminant analysis Elastic map Feature learning Growing self-organizing map (GSOM) Self-organizing map (SOM) Lawrence, Neil D (2012). "A unifying...

A self-organizing network (SON) is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile...

Kohonen's most famous contribution is the self-organizing map, or "SOM" (also known as the "Kohonen map" or "Kohonen artificial neural network"; Kohonen...

important factor to its widespread use in large neural networks. Self-organizing maps (SOMs) were described by Teuvo Kohonen in 1982. SOMs are neurophysiologically...

machines and Products of Experts. The self-organizing map (SOM) uses unsupervised learning. A set of neurons learn to map points in an input space to coordinates...

recognition and experiential learning. Among neural network models, the self-organizing map (SOM) and adaptive resonance theory (ART) are commonly used in unsupervised...

Recent efforts to enforce structure upon biomedical documents include self-organizing map approaches for identifying topics among documents, general-purpose...

The U-matrix (unified distance matrix) is a representation of a self-organizing map (SOM) where the Euclidean distance between the codebook vectors of...

Rabee; Adeloye, Adebayo J.; Scholz, Miklas (2008). "Applying Kohonen Self-Organizing Map as a Software Sensor to Predict Biochemical Oxygen Demand". Water...

the competitive learning paradigm, so it is closely related to the self-organizing map model and to sparse coding models used in deep learning algorithms...

(statistics) Manifold hypothesis Nonlinear dimensionality reduction Self-organizing map Liu, Yang; Jun, Eunice; Li, Qisheng; Heer, Jeffrey (June 2019). "Latent...

algorithm GeneRec Genetic Algorithm for Rule Set Production Growing self-organizing map Hyper basis function network IDistance k-nearest neighbors algorithm...

DBSCAN Head/tail breaks k q-flats k-means++ Linde–Buzo–Gray algorithm Self-organizing map Kriegel, Hans-Peter; Schubert, Erich; Zimek, Arthur (2016). "The...

neural networks include the Hopfield neural network and the Kohonen self-organizing map with liquid crystal spatial light modulators Optical neural networks...

skew is by abstraction in data representation. For example, in a self-organizing map (SOM), each node is a representative (a center) of a cluster of similar...

architecture (simulation) System on module, in computer embedded systems Self-organizing map, neural network in machine learning IBM System Object Model, a programming...

Self-organized criticality (SOC) is a property of dynamical systems that have a critical point as an attractor. Their macroscopic behavior thus displays...

winner-take-all Hebbian learning-based approach. It is a precursor to self-organizing maps (SOM) and related to neural gas and the k-nearest neighbor algorithm...

safety-related parameters). Data clustering techniques – such as the self-organizing map (SOM), have been applied to vibration monitoring and analysis of...

technique to construct this kind of multidimensional perceptual maps is the self-organizing map. This helps pinpoint more variables, allowing for more in-depth...

Neural gas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten. The neural...

Pseudoscience purporting to build on the principles of quantum mechanics Self-organizing map – Machine learning technique useful for dimensionality reduction...

Neural models: the most well-known unsupervised neural network is the self-organizing map and these models can usually be characterized as similar to one or...

assemblages in the Bia river-lake system (south-eastern Ivory Coast): A self-organizing map approach. Livestock Research for Rural Development. Volume 25, Article...

principle of competitive learning include vector quantization and self-organizing maps (Kohonen maps). There are three basic elements to a competitive learning...