Efficient interpretable variants of online SOM for large dissimilarity data

Results demonstrate that both approaches lead to reduce the prototypes dimensionality while providing accurate results in a reasonable computational time. Selecting one of these two strategies depends on the dataset size, the need to easily interpret the results and the computational facilities available. The conclusion tries to provide some recommendations to help the user making this choice.