I’ve trained a Linear Regression model with R caret. I’m now trying to generate a confusion matrix and keep getting the following error:
Error in confusionMatrix.default(pred, testing$Final) : the data and reference factors must have the same number of levels
EnglishMarks <- read.csv("E:/Subject Wise Data/EnglishMarks.csv", header=TRUE) inTrain<-createDataPartition(y=EnglishMarks$Final,p=0.7,list=FALSE) training<-EnglishMarks[inTrain,] testing<-EnglishMarks[-inTrain,] predictionsTree <- predict(treeFit, testdata) confusionMatrix(predictionsTree, testdata$catgeory) modFit<-train(Final~UT1+UT2+HalfYearly+UT3+UT4,method="lm",data=training) pred<-format(round(predict(modFit,testing))) confusionMatrix(pred,testing$Final)
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(pred) chr [1:148] "85" "84" "87" "65" "88" "84" "82" "84" "65" "78" "78" "88" "85" "86" "77" ... > str(testing$Final) int [1:148] 88 85 86 70 85 85 79 85 62 77 ... > levels(pred) NULL > levels(testing$Final) NULL