CODEWITHSUNDEEP
rmachine-learningnnet
Rbeginner
Rbeginner

Reputation: 3

NNet simple modeling

I'm trying to do simple neural network modelling, but the NNet result gives me poor result. It is simply ' output = 0.5 x input ' model that I want nnet model to learn, but the prediction shows all '1' as a result. What is wrong? 

library(neuralnet)
traininginput <- as.data.frame(runif(50,min=1,max=100))
trainingoutput <- traininginput/2

trainingdata<-cbind(traininginput,trainingoutput)
colnames(trainingdata)<-c("Input","Output")

net.sqrt2 <- nnet(trainingdata$Output~trainingdata$Input,size=0,skip=T, linout=T)


Testdata<-as.data.frame(1:50)
net.result2<-predict(net.sqrt2, Testdata)

cleanoutput2 <- cbind(Testdata,Testdata/2,as.data.frame(net.result2))
colnames(cleanoutput2)<-c("Input2","Expected Output2","Neural Net Output2")
print(cleanoutput2)

Upvotes: 0

Views: 442

Answers (1)

stanekam
stanekam

Reputation: 4030

library(nnet)
traininginput <- as.data.frame(runif(50,min=1,max=100))
trainingoutput <- traininginput/2

trainingdata<-cbind(traininginput,trainingoutput)
colnames(trainingdata)<-c("Input","Output")

net.sqrt2 <- nnet(Output~Input, data=trainingdata, size=0,skip=T, linout=T)


Testdata<-data.frame(Input=1:50)
net.result2<-predict(net.sqrt2, newdata = Testdata, type="raw")

cleanoutput2 <- cbind(Testdata,Testdata/2,as.data.frame(net.result2))
colnames(cleanoutput2)<-c("Input2","Expected Output2","Neural Net Output2")
print(cleanoutput2)

You're using predict and the formula in nnet wrong. Predict expects newdata which needs to be a data.frame with a column of the inputs to your model (i.e. in this case a column called Input). The formula in nnet is not to be built by literal calls on the data. It's symbolic, so it should be the names of the columns in your data. Additionally, the package you are using is not neuralnet but nnet.

Upvotes: 1

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