Abstract- We analyze the Evolving Tree, which is a tree-shaped hierarchical neural network. Especially we try to shed light on its growth process and performance when compared to classical methods. Several visualizations done with Sammon's mapping show that while the Evolving Tree describes the data set very dierently its performance is comparable to the classical methods. Key words- hierarchical clustering, tree-shaped neural networks, Evolving Tree, defect images
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...
Abstract. Roughly speaking, clustering evolving networks aims at detecting structurally dense subgro...
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...
We propose a hierarchical clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS)...
“The original publication is available at www.springerlink.com”. Copyright Springer.This paper descr...
This paper describes various mechanisms for adding stochasticity to a dynamic hierarchical neural cl...
International audienceHierarchical clustering is an important tool for extracting information from d...
SCENT is simple competitive neural network model that evolves a tree structured set of nodes in resp...
In this paper we introduce a tree structured self-organizing network, called the Growing Hierarchica...
Simmuteit S, Schleif F-M, Villmann T. Hierarchical evolving trees together with global and local lea...
Self Organising Dynamic Neural Tree Networks (DNTNs) provide hierarchical clustering that is potenti...
This paper presents TreeGNG, a top-down unsupervised learning method that produces hierarchical cla...
<p>(a) Computing Probabilities through Single Branch Evolution Technique. After extending for one ti...
The original publication is available at www.springerlink.com . Copyright Springer. DOI : 10.1023/A:...
Original article can be found at: http://www.sciencedirect.com/science/journal/08936080 Copyright El...
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...
Abstract. Roughly speaking, clustering evolving networks aims at detecting structurally dense subgro...
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...
We propose a hierarchical clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS)...
“The original publication is available at www.springerlink.com”. Copyright Springer.This paper descr...
This paper describes various mechanisms for adding stochasticity to a dynamic hierarchical neural cl...
International audienceHierarchical clustering is an important tool for extracting information from d...
SCENT is simple competitive neural network model that evolves a tree structured set of nodes in resp...
In this paper we introduce a tree structured self-organizing network, called the Growing Hierarchica...
Simmuteit S, Schleif F-M, Villmann T. Hierarchical evolving trees together with global and local lea...
Self Organising Dynamic Neural Tree Networks (DNTNs) provide hierarchical clustering that is potenti...
This paper presents TreeGNG, a top-down unsupervised learning method that produces hierarchical cla...
<p>(a) Computing Probabilities through Single Branch Evolution Technique. After extending for one ti...
The original publication is available at www.springerlink.com . Copyright Springer. DOI : 10.1023/A:...
Original article can be found at: http://www.sciencedirect.com/science/journal/08936080 Copyright El...
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...
Abstract. Roughly speaking, clustering evolving networks aims at detecting structurally dense subgro...
This paper develops a new method for hierarchical clustering. Unlike other existing clustering schem...