Some applications of unsupervised neural networks in rate making procedure

Document description

In recent years, neural networks have been having a wide range of applications. In particular, the unsupervised neural networks are designed to implement clustering techniques. In this paper we apply a two-stage Kohonen Self-Organising Map to collect the basic classes of one tariff variable in clusters. In this procedure we take advantage of the topology preservation property of the Self-Organising Maps in order to build tariff classes containing contiguous values of the tariff variable.