Work around the smoothing parameter.
A trained Probabilist neural network.
Optional. A vector giving the interval (minimum, maximum) in which the function has to search the best value.
Optional. If the value is already known, it sets directly the parameter and do not search for the best value.
smooth aims to help to set the
smoothing parameter for a Probabilist neural network. If
you have no idea of which value it can be, you can let
the function finds the best value using a genetic
algorithm. This can be done providing to the function
only the parameter
nn. This search takes some
time, so if you have already an idea of the value, you
can set it if you provide both parameters
sigma. If you want to check visually how fit is
the sigma value, you can get a plot if you provide
nn and set
plot to TRUE. It sets the
sigma of the neural network.
A trained and smoothed Probabilistic neural network.
Walter Mebane, Jr. and Jasjeet S. Sekhon. 2011. Genetic Optimization Using Derivatives: The rgenoud package for R. Journal of Statistical Software, 42(11): 1-26.
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