General regression neural network (GRNN)
GRNN is a modification of PNN for regression problems (Specht 1991). For GRNN, the predicted value of the biological property is the most probable value, which is given by
where f(x,y) is the joint density and can be estimated by using Parzen’s nonparametric estimator. Substituting Parzen’s nonparametric estimator for f(x,y) and performing the integrations leads to the fundamental equation of GRNN.
where
The network architecture of a GRNN is similar to that of a PNN except that its summation layer has two neurons that calculate the numerator and denominator. The single neuron in the output layer then performs a division of the two summation neurons to obtain the predicted biological value of the given compound.
References
- Specht DF (1991). A general regression neural network. IEEE Transactions on Neural Networks 2(6): 568-576.