I am trying to train neural networks in R using package nnet. Following is the information about my training data.
str(traindata)
'data.frame': 10327 obs. of 196 variables:
$ stars : num 5 5 5 3.5 3.5 4.5 3.5 5 5 3.5 ...
$ open : num 1 1 1 1 1 1 1 1 1 1 ...
$ city : Factor w/ 61 levels "ahwatukee","anthem",..: 36 38
$ review_count : int 3 5 4 5 14 6 21 4 14 10 ...
$ name : Factor w/ 8204 levels " leftys barber shop",..:
$ longitude : num -112 -112 -112 -112 -112 ...
$ latitude : num 33.6 33.6 33.5 33.4 33.7 ...
$ greek : int 0 0 0 0 0 0 0 0 0 0 ...
$ breakfast...brunch : int 0 0 0 0 0 0 0 0 0 0 ...
$ soup : int 0 0 0 0 0 0 0 0 0 0 ...
I have truncated this information.
When I run the following:
library(nnet)
m4 <- nnet(stars~.,data=traindata,size=10, maxit=1000)
I get the following error:
Error in nnet.default(x, y, w, ...) : too many (84581) weights
When I try changing weights in the argument like:
m4 <- nnet(stars~.,data=traindata,size=10, maxit=1000,weights=1000)
Then I get the following error:
Error in model.frame.default(formula = stars ~ ., data = traindata, weights = 1000) :
variable lengths differ (found for '(weights)')
What is the mistake I am making? How do I avoid or correct this error? Maybe the problem is with my understanding of "weights".