I find the GRNN algorithm quite interesting, as it is intuitive, fast and quite effective for small datasets with non-linear relations. The only trouble is the hyper-parameter called smoothness, or smooth or spread parameter. I wonder if there is a way to define it automaticcally (without needing a cross-validation), based on a priori knowledge on the dataset, somewhat based on data sparsity or empirical distribution for instance?