Add to ORKGAbstract. Clustering of data is one of the main applications of the Self-Organizing Map (SOM). U-matrix is a commonly used technique to cluster the SOM visually. However, in order to be really useful, clustering needs to be an automated process. There are several techniques which can be used to cluster the SOM autonomously, but the results they provide do not follow the results of U-matrix very well. In this paper, a clustering approach based on distance matrices is introduced which produces results which are very similar to the U-matrix. It is compared to other SOM-based clustering approaches.
International audienceSelf-Organizing Map (SOM) is an artificial neural network tool that is trained...
A new clustering method of a distance matrix is proposed here. The algorithm is based on the arrange...
Cluster analysis methods are used to classify R unlabeled objects in a P-dimensional space into grou...
Abstract. Clustering of data is one of the main applications of the Self-Organizing Map (SOM). U-mat...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
Clustering is to group similar objects into clusters. Until now there are a lot of approaches using ...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
International audienceIn this paper, we propose a new clustering method consisting in automated “flo...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
A powerful method in knowledge discovery and cluster extraction is the use of self-organizing maps (...
Abstract – The Self-Organizing Map (SOM) [1] is an effective tool for clustering and data mining. On...
Abstract- The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by ...
A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is ...
International audienceSelf-Organizing Map (SOM) is an artificial neural network tool that is trained...
A new clustering method of a distance matrix is proposed here. The algorithm is based on the arrange...
Cluster analysis methods are used to classify R unlabeled objects in a P-dimensional space into grou...
Abstract. Clustering of data is one of the main applications of the Self-Organizing Map (SOM). U-mat...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract – In this paper, we propose a new clustering method consisting in automated “flood- fill ...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
Clustering is to group similar objects into clusters. Until now there are a lot of approaches using ...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
International audienceIn this paper, we propose a new clustering method consisting in automated “flo...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
A powerful method in knowledge discovery and cluster extraction is the use of self-organizing maps (...
Abstract – The Self-Organizing Map (SOM) [1] is an effective tool for clustering and data mining. On...
Abstract- The Self-Organizing Map (SOM) is an unsupervised neural network introduced in the 80’s by ...
A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is ...
International audienceSelf-Organizing Map (SOM) is an artificial neural network tool that is trained...
A new clustering method of a distance matrix is proposed here. The algorithm is based on the arrange...
Cluster analysis methods are used to classify R unlabeled objects in a P-dimensional space into grou...