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#ANN demo
#Francis Roy-Desrosiers 2011-2012
require(ANN)
demo.ANN <- function() {
set.seed(1)
t <-seq(0, 2 * pi, 0.01)
#sin(t) + noise
noisy_sin <-sin(t) + 0.5 * rnorm( length(t) )
fLog <- function(x) 1/(1 + exp( -x ))
output <-matrix( fLog(noisy_sin) )
input <-matrix( seq( 0, 1, length.out=length(t) ) )
par( mfrow=c(2,2) )
plot(sin(t), main="sin")
plot(noisy_sin, main="sin + 0.5 * rnorm")
plot(output, main="sin + 0.5 * rnorm in [0,1]")
plot(input, main="input should be in the range [0,1]")
cat("\nNext step should take less than 2 minutes\n")
readline("Hit <Return> to continue")
#maxGen =10
set.seed(1)
res10<- ANNGA(x = input,
y = output,
design = c(1, 3, 1),
population = 100,
mutation = 0.2,
crossover = 0.6,
minW =-10,
maxW = 10,
maxGen = 10,
error = 0.001,
threads=2)
#maxGen =100
set.seed(1)
res100<- ANNGA(x = input,
y = output,
design = c(1, 3, 1),
population = 100,
mutation = 0.2,
crossover = 0.6,
minW =-10,
maxW = 10,
maxGen = 100,
error = 0.001,
threads=2)
#maxGen =1000
set.seed(1)
res1000<- ANNGA(x = input,
y = output,
design = c(1, 3, 1),
population = 100,
mutation = 0.2,
crossover = 0.6,
minW =-10,
maxW = 10,
maxGen = 1000,
error = 0.001,
threads=2)
par( mfrow=c(2,2) )
plot(res10)
title(sub="10 generations")
plot(res100)
title(sub="100 generations")
plot(res1000)
title(sub="1000 generations")
}
demo.ANN()
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