We are oversampling the data to use in logistic regression. Aim is to predict CTR(click probability) which is rare event scenario. I have predicted the probabilities of click but CTR results are inflated as we over sampled positive class.
model2<-SMOTE(V61 ~ ., z2, perc.over = 600,perc.under=100, learner = 'glm',family=binomial())
Is there any way to undo oversampling results so that I can get exact probabilities ? Based on research so far, one easiest way to divide the output probability by the multiplier we used in over sampling. I dont feel it would be the exact way as I have used synthetic minority over sampling technique(SMOTE) in R.