Error in ConfusionMatrix the data and reference factors must have the same number of levels
Solution 1
Try use:
confusionMatrix(table(Argument 1, Argument 2))
Thats worked for me.
Solution 2
Maybe your model is not predicting a certain factor.
Use the table()
function instead of confusionMatrix()
to see if that is the problem.
Solution 3
Try specifying na.pass
for the na.action
option:
predictionsTree <- predict(treeFit, testdata,na.action = na.pass)
Solution 4
Change them into a data frame and then use them in confusionMatrix function:
pridicted <- factor(predict(treeFit, testdata))
real <- factor(testdata$catgeory)
my_data1 <- data.frame(data = pridicted, type = "prediction")
my_data2 <- data.frame(data = real, type = "real")
my_data3 <- rbind(my_data1,my_data2)
# Check if the levels are identical
identical(levels(my_data3[my_data3$type == "prediction",1]) , levels(my_data3[my_data3$type == "real",1]))
confusionMatrix(my_data3[my_data3$type == "prediction",1], my_data3[my_data3$type == "real",1], dnn = c("Prediction", "Reference"))
user2987739
Updated on July 13, 2022Comments
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user2987739 almost 2 years
I've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the following error:
Error in confusionMatrix.default(predictionsTree, testdata$catgeory) : the data and reference factors must have the same number of levels
prob <- 0.5 #Specify class split singleSplit <- createDataPartition(modellingData2$category, p=prob, times=1, list=FALSE) cvControl <- trainControl(method="repeatedcv", number=10, repeats=5) traindata <- modellingData2[singleSplit,] testdata <- modellingData2[-singleSplit,] treeFit <- train(traindata$category~., data=traindata, trControl=cvControl, method="rpart", tuneLength=10) predictionsTree <- predict(treeFit, testdata) confusionMatrix(predictionsTree, testdata$catgeory)
The error occurs when generating the confusion matrix. The levels are the same on both objects. I cant figure out what the problem is. Their structure and levels are given below. They should be the same. Any help would be greatly appreciated as its making me cracked!!
> str(predictionsTree) Factor w/ 30 levels "16-Merchant Service Charge",..: 28 22 22 22 22 6 6 6 6 6 ... > str(testdata$category) Factor w/ 30 levels "16-Merchant Service Charge",..: 30 30 7 7 7 7 7 30 7 7 ... > levels(predictionsTree) [1] "16-Merchant Service Charge" "17-Unpaid Cheque Fee" "18-Gov. Stamp Duty" "Misc" "26-Standard Transfer Charge" [6] "29-Bank Giro Credit" "3-Cheques Debit" "32-Standing Order - Debit" "33-Inter Branch Payment" "34-International" [11] "35-Point of Sale" "39-Direct Debits Received" "4-Notified Bank Fees" "40-Cash Lodged" "42-International Receipts" [16] "46-Direct Debits Paid" "56-Credit Card Receipts" "57-Inter Branch" "58-Unpaid Items" "59-Inter Company Transfers" [21] "6-Notified Interest Credited" "61-Domestic" "64-Charge Refund" "66-Inter Company Transfers" "67-Suppliers" [26] "68-Payroll" "69-Domestic" "73-Credit Card Payments" "82-CHAPS Fee" "Uncategorised" > levels(testdata$category) [1] "16-Merchant Service Charge" "17-Unpaid Cheque Fee" "18-Gov. Stamp Duty" "Misc" "26-Standard Transfer Charge" [6] "29-Bank Giro Credit" "3-Cheques Debit" "32-Standing Order - Debit" "33-Inter Branch Payment" "34-International" [11] "35-Point of Sale" "39-Direct Debits Received" "4-Notified Bank Fees" "40-Cash Lodged" "42-International Receipts" [16] "46-Direct Debits Paid" "56-Credit Card Receipts" "57-Inter Branch" "58-Unpaid Items" "59-Inter Company Transfers" [21] "6-Notified Interest Credited" "61-Domestic" "64-Charge Refund" "66-Inter Company Transfers" "67-Suppliers" [26] "68-Payroll" "69-Domestic" "73-Credit Card Payments" "82-CHAPS Fee" "Uncategorised"