Introduction In this post I will be creating a predictive model to identify fraudulent credit card transactions on a public data set from kaggle. Along the way, I will be reviewing some of the functionality of R’s gbm package for predictive modelling. Data Overview The data set contiains 280K+ records of credit card transactions from a two-week period in which a small percentage of transactions have been labeled as fraudulent.