neuralnet (version 1.33)

compute: Computation of a given neural network for given covariate vectors

Description

compute, a method for objects of class nn, typically produced by neuralnet. Computes the outputs of all neurons for specific arbitrary covariate vectors given a trained neural network. Please make sure that the order of the covariates is the same in the new matrix or dataframe as in the original neural network.

Usage

compute(x, covariate, rep = 1)

Arguments

x

an object of class nn.

covariate

a dataframe or matrix containing the variables that had been used to train the neural network.

rep

an integer indicating the neural network's repetition which should be used.

Value

compute returns a list containing the following components:

neurons

a list of the neurons' output for each layer of the neural network.

net.result

a matrix containing the overall result of the neural network.

Examples

# NOT RUN {
Var1 <- runif(50, 0, 100) 
sqrt.data <- data.frame(Var1, Sqrt=sqrt(Var1))
print(net.sqrt <- neuralnet(Sqrt~Var1,  sqrt.data, hidden=10, 
                  threshold=0.01))
compute(net.sqrt, (1:10)^2)$net.result
# }

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