A general regression neural network

@article{Specht1991AGR,
  title={A general regression neural network},
  author={Donald F. Specht},
  journal={IEEE transactions on neural networks},
  year={1991},
  volume={2 6},
  pages={568-76}
}
A memory-based network that provides estimates of continuous variables and converges to the underlying (linear or nonlinear) regression surface is described. The general regression neural network (GRNN) is a one-pass learning algorithm with a highly parallel structure. It is shown that, even with sparse data in a multidimensional measurement space, the algorithm provides smooth transitions from one observed value to another. The algorithmic form can be used for any regression problem in which… CONTINUE READING
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