Description Usage Arguments Details Value See Also Examples

Neural Networks

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`dataset` |
Dataset |

`rvar` |
The response variable in the model |

`evar` |
Explanatory variables in the model |

`type` |
Model type (i.e., "classification" or "regression") |

`lev` |
The level in the response variable defined as _success_ |

`size` |
Number of units (nodes) in the hidden layer |

`decay` |
Parameter decay |

`wts` |
Weights to use in estimation |

`seed` |
Random seed to use as the starting point |

`check` |
Optional estimation parameters ("standardize" is the default) |

`data_filter` |
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000") |

See https://radiant-rstats.github.io/docs/model/nn.html for an example in Radiant

A list with all variables defined in nn as an object of class nn

`summary.nn`

to summarize results

`plot.nn`

to plot results

`predict.nn`

for prediction

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