Author(s): P. Lakatos, B. Egri & P. Aszalós
Retail bank customer relationships, like many systems observed in real life,
cannot be modelled deterministically - they have multiple variables,
interdependent through various channels of cause and effect and are subject to
The methods used with such data extract a model by
uncovering stochastic relationships between variables.
Networks accomplish this effectively because they are capable of integrating
experts' knowledge, discovering causal relationships in the data and introducing
hidden variables to represent exogenous effects.
In this paper we present a
method of building a customer relationship model using Bayesian Belief
In addition, we emphasise the need to use concepts employed by compa...
Size: 378 kb
Paper DOI: 10.2495/DATA030231
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