问题
I have a training set that looks like
Name Day Area X Y Month Night
ATTACK Monday LA -122.41 37.78 8 0
VEHICLE Saturday CHICAGO -1.67 3.15 2 0
MOUSE Monday TAIPEI -12.5 3.1 9 1
Name is the outcome/dependent variable. I converted Name, Area and Day into factors, but I wasn't sure if I was supposed to for Month and Night, which only take on integer values 1-12 and 0-1, respectively.
I then convert the data into matrix
ynn <- model.matrix(~Name , data = trainDF)
mnn <- model.matrix(~ Day+Area +X + Y + Month + Night, data = trainDF)
I then setup tuning the parameters
nnTrControl=trainControl(method = "repeatedcv",number = 3,repeats=5,verboseIter = TRUE, returnData = FALSE, returnResamp = "all", classProbs = TRUE, summaryFunction = multiClassSummary,allowParallel = TRUE)
nnGrid = expand.grid(.size=c(1,4,7),.decay=c(0,0.001,0.1))
model <- train(y=ynn, x=mnn, method='nnet',linout=TRUE, trace = FALSE, trControl = nnTrControl,metric="logLoss", tuneGrid=nnGrid)
However, I get the error Error: nrow(x) == n is not TRUE for the model<-train
I also get a similar error if I use xgboost instead of nnet
Anyone know whats causing this?
回答1:
y should be a numeric or factor vector containing the outcome for each sample, not a matrix. Using
train(y = make.names(trainDF$Name), ...)
helps, where make.names modifies values so that they could be valid variable names.
回答2:
Even though in the help file of train said either maxtrix or data frame would be expected, but you can try to convert the matrix to a data frame:
model <- train(y=ynn, x=as.data.frame(mnn), method='nnet',linout=TRUE, trace = FALSE, trControl = nnTrControl,metric="logLoss", tuneGrid=nnGrid)
来源：https://stackoverflow.com/questions/35527492/error-nrowx-n-is-not-true-when-using-train-in-caret