R caret train Error in evalSummaryFunction: cannnot compute class probabilities for regression

Question

> cv.ctrl <- trainControl(method = \"repeatedcv\", repeats = 3,
+                         summaryFunction = twoClassSummary,
+                         classPro         


        

Answer 1

If you changed the values in y to "YES" and "NO" instead of 1 and zero respectively, then the code will run.

y=ifelse(train.batch$y==0,"No","Yes")

Answer 2

Apparently this error is due to the fact that my y is not a Factor.

Following code works fine:

library(caret)
library(mlbench)
data(Sonar)

ctrl <- trainControl(method = "cv", 
                     summaryFunction = twoClassSummary, 
                     classProbs = TRUE)
set.seed(1)
gbmTune <- train(Class ~ ., data = Sonar,
                 method = "gbm",
                 metric = "ROC",
                 verbose = FALSE,                    
                 trControl = ctrl)

Then doing:

Sonar$Class = as.numeric(Sonar$Class)

and same code throws the error:

> gbmTune <- train(Class ~ ., data = Sonar,
+                  method = "gbm",
+                  metric = "ROC",
+                  verbose = FALSE,                    
+                  trControl = ctrl)
Error in evalSummaryFunction(y, trControl, classLevels, metric, method) : 
  train()'s use of ROC codes requires class probabilities. See the classProbs option of trainControl()
In addition: Warning message:
In train.default(x, y, weights = w, ...) :
  cannnot compute class probabilities for regression

But caret train documentation says:

y   a numeric or factor vector containing the outcome for each sample.