Add to ORKGAbstract. The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A theoretical and practical challenge in the SOM has been the difficulty to treat the method as a statistical model fitting procedure. In this chapter we give a short review of statistical approaches for the SOM. Then we present the probability density model for which the SOM training gives the maximum likelihood estimate. The density model can be used to choose the neighborhood width of the SOM so as to avoid overfitting and to improve the reliability of the results. The density model also gives tools for systematic analysis of the SOM. A major application of the SOM is the analysis of dependencies between variables. We discuss some difficulties in ...
Accepted for publication in Neural Computation. Latent variable models represent the probability den...
The self-organizing mixture network (SOMN) is a learning algorithm for mixture densities, derived fr...
The Self-Organizing Maps (SOM) is a very popular algorithm, introduced by Teuvo Kohonen in the early...
The Self-OrganizingMap (SOM) algorithm has been extensively studied and has been applied with consid...
The Self-Organizing Map (SOM) algorithm has been extensively studied and has been applied with consi...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation a...
Results of neural network learning are always subject to some variability, due to the sensitivity to...
Self-organizing maps (SOM) are among the more popular neural network models first studied by Teuvo K...
The generative topographic mapping (GTM) model was introduced by Bishop et al. (1998, Neural Comput....
Abstract Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in da...
A self-organizing mixture network (SOMN) is derived for learning arbitrary density functions. The ne...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
The self-organizing map (SOM) is a nonlinear unsupervised method for vector quantization. In the con...
The S-Map is a network with a simple learning algorithm that combines the self-organization capabili...
Abstract—A self-organizing mixture network (SOMN) is derived for learning arbitrary density function...
Accepted for publication in Neural Computation. Latent variable models represent the probability den...
The self-organizing mixture network (SOMN) is a learning algorithm for mixture densities, derived fr...
The Self-Organizing Maps (SOM) is a very popular algorithm, introduced by Teuvo Kohonen in the early...
The Self-OrganizingMap (SOM) algorithm has been extensively studied and has been applied with consid...
The Self-Organizing Map (SOM) algorithm has been extensively studied and has been applied with consi...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation a...
Results of neural network learning are always subject to some variability, due to the sensitivity to...
Self-organizing maps (SOM) are among the more popular neural network models first studied by Teuvo K...
The generative topographic mapping (GTM) model was introduced by Bishop et al. (1998, Neural Comput....
Abstract Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in da...
A self-organizing mixture network (SOMN) is derived for learning arbitrary density functions. The ne...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
The self-organizing map (SOM) is a nonlinear unsupervised method for vector quantization. In the con...
The S-Map is a network with a simple learning algorithm that combines the self-organization capabili...
Abstract—A self-organizing mixture network (SOMN) is derived for learning arbitrary density function...
Accepted for publication in Neural Computation. Latent variable models represent the probability den...
The self-organizing mixture network (SOMN) is a learning algorithm for mixture densities, derived fr...
The Self-Organizing Maps (SOM) is a very popular algorithm, introduced by Teuvo Kohonen in the early...