ctrl <- trainControl(method = "repeatedcv",
                     number = 10,
                     repeats = 10,
                     search = "grid",
                     returnData = TRUE,
                     returnResamp = "final",
                     savePredictions = "all",
                     classProbs = TRUE,
                     sampling = "smote",
                     summaryFunction = twoClassSummary,
                     selectionFunction = "best",
                     allowParallel = TRUE)

library(caret)
library(DMwR)

set.seed(2969)
imbal_train <- twoClassSim(10000, intercept = -20, linearVars = 20)
table(imbal_train$Class)

set.seed(9560)
smote_train <- SMOTE(Class ~ ., data  = imbal_train)
table(smote_train$Class)[2]

perc.over <- 100*(table(smote_train$Class)[2]-table(imbal_train$Class)[2])/table(imbal_train$Class)[2]
perc.under <- 100*table(smote_train$Class)[1]/(table(smote_train$Class)[2]-table(imbal_train$Class)[2])

set.seed(1234)
imbal_train <- twoClassSim(10000, intercept = -40, linearVars = 40)
table(imbal_train$Class)

set.seed(5678)
smote_train <- SMOTE(Class ~ ., data  = imbal_train)
table(smote_train$Class)

perc.over <- 100*(table(smote_train$Class)[2]-table(imbal_train$Class)[2])/table(imbal_train$Class)[2]
perc.under <- 100*table(smote_train$Class)[1]/(table(smote_train$Class)[2]-table(imbal_train$Class)[2])