Abstract This paper proposes a novel variable learning rate to address two main challenges of the conventional Self-Organizing Maps (SOM) termed VLRSOM: high accuracy with fast convergence and low topological error. We empirically showed that proposed method exhibits faster behavior. It is also more robust in topology preservation as it maintains an optimal until end maximum iterations. Since a...