r language getting a not so good neural network - r

Question

i am trying to fit a neural net using nnet method. But for some reason i am getting fitted values =1 . any suggestion?
traininginput <- as.data.frame(runif(50, min=0, max=100))
trainingoutput <- sqrt(traininginput)
#Column bind the data into one variable
trainingdata <- cbind(traininginput,trainingoutput)
colnames(trainingdata) <- c("Input","Output")
nnet1=nnet(trainingdata$Input,trainingdata$Output,size=10,decay=.2,MaxNWts=100)
nnet1=nnet(trainingdata$Input,trainingdata$Output,size=10,decay=.2,MaxNWts=100)
# weights: 31
initial value 2398.911170
iter 10 value 1881.721970
iter 20 value 1879.273609
iter 30 value 1879.248746
final value 1879.248003
converged
nnet1$fitted.values
[,1]
[1,] 0.9995635611
[2,] 0.9995572993
[3,] 0.9994755520
[4,] 0.9995623911
[5,] 0.9946006508
[6,] 0.9995635779
[7,] 0.9995108061
[8,] 0.9995635025
[9,] 0.9995634973
[10,] 0.9993213029
[11,] 0.9994652808
[12,] 0.9979116411
[13,] 0.9993242430
[14,] 0.9995635764
[15,] 0.9995632595
[16,] 0.9995583546
[17,] 0.9992778848
[18,] 0.9995635364
[19,] 0.9939526885
[20,] 0.9995635788
[21,] 0.9993010783
[22,] 0.9995597586
[23,] 0.9995635748
[24,] 0.9995635799
[25,] 0.9995634813
[26,] 0.9992898229
[27,] 0.9959834977
[28,] 0.9991941868
[29,] 0.9995632224
[30,] 0.9995486025
[31,] 0.9995608608
[32,] 0.9995635755
[33,] 0.9995635740
[34,] 0.9995491922
[35,] 0.9995635661
[36,] 0.9995629924
[37,] 0.9995634948
[38,] 0.9994889240
[39,] 0.9995633558
[40,] 0.9995559725
[41,] 0.9995563696
[42,] 0.9995564636
[43,] 0.9995602699
[44,] 0.9995635768
[45,] 0.9995612253
[46,] 0.9895069469
[47,] 0.9995271104
[48,] 0.9995635564
[49,] 0.9995635797
[50,] 0.9995609961

Answer 1

Add the linout = TRUE argument to the nnet function:
nnet1=nnet(trainingdata$Input,trainingdata$Output,size=10,decay=.2,MaxNWts=100, linout = TRUE)
That should solve your problem! By default, the fitted values are logistic output units - see ?nnet.