3 papers with code • 0 benchmarks • 0 datasets
Clustering with Self-Organized Maps
These leaderboards are used to track progress in Self-Organized Clustering
In the wake of recent advances in joint clustering and deep learning, we introduce the Deep Embedded Self-Organizing Map, a model that jointly learns representations and the code vectors of a self-organizing map.
Furthermore, an important and very promising application of GH-EXIN in two-way hierarchical clustering, for the analysis of gene expression data in the study of the colorectal cancer is described.
Quantitative evaluation of self-organizing maps (SOM) is a subset of clustering validation, which is a challenging problem as such.