nn_model

0th

Percentile

nn_model

generates the code to create the neural network model.

Usage
nn_model(data = "datos.aprendizaje", variable.pred = NULL,
  model.var = "modelo.nn", mean.var = "mean.nn", sd.var = "sd.nn",
  threshold = 0.01, stepmax = 1000, cant.hidden = 2, ...)
Arguments
data

the name of the learning data.

variable.pred

the name of the variable to be predicted.

model.var

the name of the variable that stores the resulting model.

mean.var

the name of the variable that stores the mean of the columns.

sd.var

the name of the variable that stores the standard deviation of the columns.

threshold

the threshold parameter of the model.

stepmax

the stepmax parameter of the model.

cant.hidden

the quantity of hidden layers that are going to be used.

...

a vector with the number of nodes in each hidden layer.

See Also

neuralnet

Aliases
  • nn_model
Examples
# NOT RUN {
library(neuralnet)
library(dummies)

x <- nn_model('iris', 'Petal.Length','modelo.nn', 'mean.nn', 'sd.nn', 0.05, 2000, 3, 30, 50, 80)
exe(x)

print(modelo.nn)
print(mean.nn)
print(sd.nn)
# }
Documentation reproduced from package regressoR, version 1.1.7, License: GPL (>= 2)

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