1. A computer-implemented method for building an artificial neural network, wherein the artificial neural network predicts at least one target based upon observations defined in a state space, comprising the steps of: retrieving an input data set that includes the observations and the target; inserting in the state space a plurality of points based upon the values of the observations in the state space, wherein the number of inserted points is less than the number of observations; determining a statistical measure that describes a relationship between the observations and the inserted points; and determining weights and activation functions of the artificial neural network using the statistical measure.