I have the following model to predict the price of houses in a particular neighborhood :
set.seed(100)
index_1<-sample(1:nrow(data),round(nrow(data)*0.9))
train<-data[index_1,] #578 obs.
test<-data[-index_1,] #62 obs.
NModel <- neuralnet(price ~ x1 + x2 + x3 + x4, data=train_group, hidden=c(5), linear.output=FALSE, threshold =0.01, rep=20, learningrate = 0.25 )
However I have been changing my learning rate from 0.25 to 1 and nothing has changed on my RMSE. It neither gets worse nor gets better, it stays exactly the same, even when changing a learning rate. Does anyone have any hints of what may be happening?
neuralnet function | R Documentation
learningrate is used only for traditional backpropagation. Try adding the argument algorithm = 'backprop' and then see what different values for learningrate do.