We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the origin...
In this paper, a new method for the determination of missing values in temporal databases is presented. This new method is based on two projection methods: a nonlinear one (Self-Or...
Antti Sorjamaa, Paul Merlin, Bertrand Maillet, Ama...
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
This work proposes a theoretical guideline in the specific area of Frequent Itemset Mining (FIM). It supports the hypothesis that the use of neural network technology for the prob...
In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. Th...