amberpearl92

library(nnet)

apm <- matrix(AirPassengers, ncol = 12, byrow =TRUE, dimnames = list( as.character(1949:1960),month.abb))

AirPassengers.train<-apm[c(1,10),]

AirPassengers.test<-apm[c(11,12),]

mynnet.fit<-nnet(Dec~.,data=apm,subset=AirPassengers.train,size=5,maxit=1000)

mynnet.predict<-predict(mynnet.fit,AirPassengers.test)

predict.rmse<-sqrt(mean((mynnet.predict-AirPassengers.test[,12])^2))

cbind(AirPassengers.test[,12],mynnet.predict)

that is all my code here are the output problems:

1.net.fit<-nnet(Dec~.,data=apm,subset=AirPassengers.train,size=5,maxit=1000)

# weights: 66

initial value 0.000000

final value 0.000000

converged

why is the initial value 0??

2.nd(AirPassengers.test[,12],mynnet.predict)

[,1] [,2]

1959 405 0.5942836

1960 432 0.5942836

you see the prediction is nowhere near the real values.

AirPassengers is one of the data sets R comes with.

HELP!!! This project has been driving me crazy for weeks. These few lines of code just won't work for me.

:D

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