BiodiversityR (version 1.5)

nnetrandom: Calculate the NNET Result with the Smallest Value from Various Random Starts

Description

This function provides the best solution from various calls to the nnet feed-forward artificial neural networks function (nnet).

Usage

nnetrandom(formula,data,tries=10,leave.one.out=F,...)

Arguments

formula

Formula as passed to nnet.

data

Data as passed to nnet.

tries

Number of calls to nnet to obtain the best solution.

leave.one.out

Calculate leave-one-out predictions.

...

Other arguments passed to nnet.

Value

• The function returns the same components as nnet, but adds the following components:
• range
  Summary of the observed "values".
• tries
  Number of different attempts to iterate an ANN.
• CV
  Predicted class when not using the respective sample unit for iterating ANN.
• succesful
  Test whether leave-one-out statistics provided the same class as the original class.

Details

This function makes various calls to nnet. If desired by the user, leave-one-out statistics are provided that report the prediction if one particular sample unit was not used for iterating the networks.

Examples

data(faramea)
faramea <- na.omit(faramea)
faramea$presence <- as.numeric(faramea$Faramea.occidentalis > 0)
attach(faramea)
library(nnet)
result <- nnetrandom(presence ~ Elevation, data=faramea, size=2, 
    skip=FALSE, entropy=TRUE, trace=FALSE, maxit=1000, tries=100, 
    leave.one.out=FALSE)
summary(result)
result$fitted.values
result$value
result2 <- nnetrandom(presence ~ Elevation, data=faramea, size=2, 
    skip=FALSE, entropy=TRUE, trace=FALSE, maxit=1000, tries=50, 
    leave.one.out=TRUE)
result2$range
result2$CV
result2$successful