Saving output of confusionMatrix as a .csv table

Question

I have a following code resulting in a table-like output

 lvs <- c("normal", "abnormal")
 truth <- factor(rep(lvs, times = c(86, 258)),
                 levels = rev(lvs))
 pred <- factor(
                c(
                  rep(lvs, times = c(54, 32)),
                  rep(lvs, times = c(27, 231))),               
                levels = rev(lvs))

 xtab <- table(pred, truth)

 library(caret)
 confusionMatrix(xtab)

 confusionMatrix(pred, truth)
 confusionMatrix(xtab, prevalence = 0.25)   

I would like to export the below part of the output as a .csv table

               Accuracy : 0.8285          
                 95% CI : (0.7844, 0.8668)
    No Information Rate : 0.75            
    P-Value [Acc > NIR] : 0.0003097       

                  Kappa : 0.5336          
 Mcnemar's Test P-Value : 0.6025370       

            Sensitivity : 0.8953          
            Specificity : 0.6279          
         Pos Pred Value : 0.8783          
         Neg Pred Value : 0.6667          
             Prevalence : 0.7500          
         Detection Rate : 0.6715          
   Detection Prevalence : 0.7645          
      Balanced Accuracy : 0.7616  

Attempt to write it as a .csv table results in the error message:

write.csv(confusionMatrix(xtab),file="file.csv")
Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : 
cannot coerce class ""confusionMatrix"" to a data.frame

Doing the whole work manually, for obvious reasons, is impractical and prone to human errors.

Any suggestions on how to export it as a .csv?

Answer 1

Ok, so if you inspect the output of confusionMatrix(xtab, prevalence = 0.25) , it's a list:

cm <- confusionMatrix(pred, truth)
str(cm)

    List of 5
 $ positive: chr "abnormal"
 $ table   : 'table' int [1:2, 1:2] 231 27 32 54
  ..- attr(*, "dimnames")=List of 2
  .. ..$ Prediction: chr [1:2] "abnormal" "normal"
  .. ..$ Reference : chr [1:2] "abnormal" "normal"
 $ overall : Named num [1:7] 0.828 0.534 0.784 0.867 0.75 ...
  ..- attr(*, "names")= chr [1:7] "Accuracy" "Kappa" "AccuracyLower" "AccuracyUpper" ...
 $ byClass : Named num [1:8] 0.895 0.628 0.878 0.667 0.75 ...
  ..- attr(*, "names")= chr [1:8] "Sensitivity" "Specificity" "Pos Pred Value" "Neg Pred Value" ...
 $ dots    : list()
 - attr(*, "class")= chr "confusionMatrix"

From here on you select the appropriate objects that you want to create a csv from and make a data.frame that will have a column for each variable. In your case, this will be:

tocsv <- data.frame(cbind(t(cm$overall),t(cm$byClass)))

# You can then use
write.csv(tocsv,file="file.csv")