问题
I have a training dataset
Out Revolver Ratio Num ...
0 1 0.766127 0.802982 0 ...
1 0 0.957151 0.121876 1
2 0 0.658180 0.085113 0
3 0 0.233810 0.036050 3
4 1 0.907239 0.024926 5
The outcome variable Out is binary and only takes on the values 0 or 1. Num is not a factor
I then attempted to run nnet using caret. I want to eventually try nnGrid but I just want to make sure this works first:
nnTrControl=trainControl(method = "cv", classProbs = TRUE, summaryFunction = twoClassSummary,
number = 2,verboseIter = TRUE, returnData = FALSE, returnResamp = "all")
#nnGrid = expand.grid(.size=c(1,4,7),.decay=c(0,0.001,0.1))
Outf<-factor(training$Out)
model <- train(Outf~ Revolver+Ratio+Num, data=training, method='nnet',
trControl = nnTrControl, metric="logLoss")#, tuneGrid=nnGrid)
I get the error
Error in train.default(x, y, weights = w, ...) :
At least one of the class levels is not a valid R variable name; This will cause errors when class probabilities are generated because the variables names will be converted to X0, X1 . Please use factor levels that can be used as valid R variable names (see ?make.names for help).
However, I've used caret and gotten this error before, which I resolved by using make.names. So when I try the below instead:
yCat<-make.names(training$Out, unique=FALSE, allow_=TRUE)
mnn <- model.matrix( ~Revolver + Ratio + Num, data = training)
model <- train(y=yCat, x=mnn, method='nnet',
trControl = nnTrControl, metric="logLoss")#, tuneGrid=nnGrid)
I then get the message
The metric "logLoss" was not in the result set. ROC will be used instead.
But I don't understand why its not evaluating according to logLoss?
If I then use this to predict on a test set
probs<-predict(model, newdata=testSet, type="prob")
I get
Error in eval(expr, envir, enclos) : object '(Intercept)' not found
How do I fix this?
来源：https://stackoverflow.com/questions/35569705/caret-nnet-logloss-not-working-for-twoclasssummary