Split Training Data and Add Aggregated Features
The data is first split into a training subset. From that subset, the workflow creates two summary features: one that captures how often a key value appears, and another that summarizes activity across a time-related grouping. These summaries are then joined back to each training row, so each record keeps its original details while gaining extra context about how common its group is and the broader pattern it belongs to.
