Description Usage Arguments Details Value References See Also Examples

Work around the smoothing parameter.

1 |

`nn` |
A trained Probabilist neural network. |

`limits` |
Optional. A vector giving the interval (minimum, maximum) in which the function has to search the best value. |

`sigma` |
Optional. If the value is already known, it sets directly the parameter and do not search for the best value. |

The function `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 `nn`

and
`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
parameters `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.

`pnn-package`

, `learn`

,
`perf`

, `guess`

,
`norms`

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