Add to ORKGThe Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
Self-organizing maps are an unsupervised machine learning technique that offers interpretable result...
High dimensional data visualization is one of the main tasks in the field of data mining and pattern...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
Mapping quality of the self-organising maps (SOMs) is sensitive to the map topology and initialisati...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning and visuali...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. However, d...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning and visuali...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clu...
Self-organizing maps are an unsupervised machine learning technique that offers interpretable result...
High dimensional data visualization is one of the main tasks in the field of data mining and pattern...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
Mapping quality of the self-organising maps (SOMs) is sensitive to the map topology and initialisati...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning and visuali...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. However, d...
Abstract — The Self-Organizing Map (SOM) is popular algo-rithm for unsupervised learning and visuali...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...