library(neuralnet)

mix = read.csv("mix.csv",sep=';')

nn = neuralnet(
  acid~qH+qO+qOd,
  data=mix,
  hidden = c(10,5,3,5),
  linear.output = F)

mix$npKa = scale(
  mix$pKa, 
  center = min(mix$pKa), 
  scale = max(mix$pKa) - min(mix$pKa)
  )

nn = neuralnet(
  npKa~qH+qO+qOd,
  data=mix,
  hidden = c(5),
  linear.output = T,
  rep = 5,
  threshold = .0001)

npred <- compute(nn,mix[,6:8])
pred <- npred$net.result*(
  max(mix$pKa)-min(mix$pKa))+min(mix$pKa)

plot(npred$net.result,mix$npKa)

ntrain <- scaled[-s,]
ntest <- scaled[s,]