the predictive modeling process is a form of automated data crunching that learns from training examples, which must include both positive and negative examples. An organization needs to have positively identified in the past some cases of what it would like to predict in the future. To predict something like “Will buy a stereo,” you can bet a retailer has plenty of positive cases. But how can you locate Target customers known to be pregnant?
