machine learning – R neuralNet: non-conformable arguments

machine learning – R neuralNet: non-conformable arguments

It looks like you need to remove the predictor variable. Try this:

nn_pred<-compute(nn,test[,3:11])

I tried this with the neuralnet package as well. I think if you instead of

net.results <- compute(
  net, matrix.train2

do

net.result <- compute(  
     net, matrix.train2[,c(pclass,   
     sexmale, age, sibsp, parch,   
     fare,embarkedC,embarkedQ,embaredS)])

it should work. The names of the variables needs to be in the exact order of the model.list$variables, so you can also type

net.result <- compute(  
     net, matrix.train2[, net.result$model.list$variables])

I hope this helps. The reason is – I think – that neuralnet has a problem finding out which variables are in your net and which in the matrix… so you match them explicitly instead.

machine learning – R neuralNet: non-conformable arguments

I havent used the neuralnet ackage, but unless its doing something weird you shouldnt be calling model.matrix like that. neuralnet has a formula interface, so it will call model.matrix for you. You just have to give it the training data frame train1.

This also applies for predicting on test data. Dont create a model matrix; just pass it the data frame train2.