KLN, a new biological koniocortex based unsupervised neural network: competitive results on credit scoring

Abstract

Koniocortex-Like Network (KLN) model is a Bio-Inspired Neural Network structure that tries to replicate the architecture and properties of the biological koniocortex section of the brain. Based on its biological counterpart that behaves as a Winner-Take-All competitive system, this new structure is composed by different kind of artificial neurons that interplay naturally between them to create a model able to map autonomously the intrinsic knowledge included in a dataset into different classes. Biological properties of the human neural system as metaplasticity and intrinsic plasticity have been translated into this artificial model to create a self-organizing system applicable to multiple disciplines. This approach leads to a natural evolution of the network’s dynamics until obtaining the desired results. The KLN has been previously tested on several synthetic and real datasets, in this article we check its capability to deal with a different type of information by applying it to credit scoring problem, in particular to the classification of credit data from the Australian Credit Approval Database.