Add to ORKGapplication/pdfSelf－Organizing Maps trained using unsupervised learning to produce a two－dimensional discredited representation of input space of the training cases. Growing－Hierarchical SOM is an architecture which grows both in a hierarchical way representating the structure of data distribution, and in a horizontal way representating the size of each individual maps. The control method of the growing degree of GHSOM by pruning off the redundant branch of hierarchy in SOM was proposed in the fuzzy work shop2010. In this paper，the interface tool for the proposed method called interactive GHSOM is developed. We discuss the computation results of Iris data by using the developed tool．開催日 : 2011年3月18日-19日 会場 : 首都大学東
Self-organizing maps (SOMs) have become popular for tasks in data visualization, pattern classificat...
We propose a hierarchical self-organizing neural network ( HiGS ) with adaptive architecture and sim...
The Self-Organizing Map is a very popular unsupervised neural network model for the analysis of high...
Self－Organizing Maps trained using unsupervised learning to produce a two－dimensional discredited re...
application/pdfSelf Organizing Map is trained using unsupervised learning to produce a two dimension...
A self organizing map (SOM) is trained using unsupervised learning to produce a twodimensional discr...
AbstractThe use of self-organising maps (SOM) in unsupervised knowledge discovery has been successfu...
In this paper we introduce a tree structured self-organizing network, called the Growing Hierarchica...
This work presents a neural network model for the clustering analysis of data based on Self Organizi...
Abstract. The Growing Hierarchical Self Organizing Map (GHSOM) was introduced as a dynamical neural ...
This paper proposes an extension of the self-organizing map (SOM), in which the mapping objects them...
The Growing Hierarchical Self-Organizing Map (GHSOM) algorithm has shown its potential for performin...
The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high...
Abstract:- The Self-Organizing Map (SOM) has shown to be a stable neural network model for high- dim...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning introduced ...
Self-organizing maps (SOMs) have become popular for tasks in data visualization, pattern classificat...
We propose a hierarchical self-organizing neural network ( HiGS ) with adaptive architecture and sim...
The Self-Organizing Map is a very popular unsupervised neural network model for the analysis of high...
Self－Organizing Maps trained using unsupervised learning to produce a two－dimensional discredited re...
application/pdfSelf Organizing Map is trained using unsupervised learning to produce a two dimension...
A self organizing map (SOM) is trained using unsupervised learning to produce a twodimensional discr...
AbstractThe use of self-organising maps (SOM) in unsupervised knowledge discovery has been successfu...
In this paper we introduce a tree structured self-organizing network, called the Growing Hierarchica...
This work presents a neural network model for the clustering analysis of data based on Self Organizi...
Abstract. The Growing Hierarchical Self Organizing Map (GHSOM) was introduced as a dynamical neural ...
This paper proposes an extension of the self-organizing map (SOM), in which the mapping objects them...
The Growing Hierarchical Self-Organizing Map (GHSOM) algorithm has shown its potential for performin...
The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high...
Abstract:- The Self-Organizing Map (SOM) has shown to be a stable neural network model for high- dim...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning introduced ...
Self-organizing maps (SOMs) have become popular for tasks in data visualization, pattern classificat...
We propose a hierarchical self-organizing neural network ( HiGS ) with adaptive architecture and sim...
The Self-Organizing Map is a very popular unsupervised neural network model for the analysis of high...