Afficher la couverture 'Theoretical and applied aspects of the self-organizing maps | Cottrell, Marie' en grand format
/5

0 avis

Theoretical and applied aspects of the self-organizing maps

Archive ouverte

Cottrell, Marie | Olteanu, Madalina | Rossi, Fabrice | Vialaneix, Nathalie

Edité par CCSD ; Springer International Publishing Switzerland -

International audience. The Self-Organizing Map (SOM) is widely used, easy to implement , has nice properties for data mining by providing both clustering and visual representation. It acts as an extension of the k-means algorithm that preserves as much as possible the topological structure of the data. However, since its conception, the mathematical study of the SOM remains difficult and has be done only in very special cases. In WSOM 2005, Jean-Claude Fort presented the state of the art, the main remaining difficulties and the mathematical tools that can be used to obtain theoretical results on the SOM outcomes. These tools are mainly Markov chains, the theory of Ordinary Differential Equations, the theory of stability , etc. This article presents theoretical advances made since then. In addition, it reviews some of the many SOM algorithm variants which were defined to overcome the theoretical difficulties and/or adapt the algorithm to the processing of complex data such as time series, missing values in the data, nominal data, textual data, etc.

Suggestions

Du même auteur

Neural Networks for Complex Data

Archive ouverte | Cottrell, Marie | CCSD

International audience. Artificial neural networks are simple and efficient machine learning tools. Defined originally in the traditional setting of simple vector data, neural network models have evolved to address ...

Accelerating stochastic kernel SOM

Archive ouverte | Mariette, Jérôme, J. | CCSD

International audience. Analyzing non vectorial data has become a common trend in a number of real-life applications. Various prototype-based methods have been extended to answer this need by means of kernalization ...

On-line relational SOM for dissimilarity data

Archive ouverte | Olteanu, Madalina | CCSD

International audience. In some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilari...

Chargement des enrichissements...