nn_prediction

0th

Percentile

nn_prediction

generates the code to create the prediction of the neural network model.

Usage
nn_prediction(data = "datos.prueba", variable.pred = NULL,
  model.var = "modelo.nn", pred.var = "prediccion.nn",
  mean.var = "mean.nn", sd.var = "sd.nn")
Arguments
data

the name of the test data.

variable.pred

the name of the variable to be predicted.

model.var

the name of the variable that stores the resulting model.

pred.var

the name of the variable that stores the resulting prediction.

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.

See Also

compute

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

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

x <- nn_prediction('iris', 'Petal.Length')
exe(x)
print(prediccion.nn)
# }
Documentation reproduced from package regressoR, version 1.1.7, License: GPL (>= 2)

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