predicting class for new data using neuralnet

Question

I\'m trying to predict the class (0 or 1) for a test dataset using a neural network trained using the neuralnet package in R.

The data I have looks as follows:

Answer 1

Hard to say in the absence of a good description of the 'test'-object, but can you see if this gives better results:

compute(nn, test[, 1:4])

Answer 2

I know this is an old post, but I came across a unique piece that may help someone in the future. Thought this post was most applicable as it throws the same error.

Scaling of a dataset must be converted back into a data.frame for use in compute

#scaled data
scaledData=scale(data)
nn=neuralnet(y~x,data=scaledData[train,])

#this repeatedly failed for me
compute(nn,scaledData[test,])

#this worked 
compute(nn,as.data.frame(scaledData)[test,])

Answer 3

I had the same problem. I put debugonce(neuralnet) and I discovered neuralnet was multiplying matrix from different sizes.

I solved the problem removing the y column from test with this function

columns <- c("x1","x2","x3","x4")
covariate <- subset(test, select = columns)