6. Suppose we are running a fraud classification model, with a training set of 10,000 records of which only 400 are fraudulent. a) How many fraudulent records need to be resampled if we would like the proportion of fraudulent records in the balanced data set to be 20%? b) How many non-fraudulent records need to be set aside if we would like the proportion of fraudulent records in the balanced data set to be 20%?