The 15 Techniques
1. Target Encoding (with smoothing)
smoothed = (count * category_mean + global_mean * smoothing) / (count + smoothing)
2. Frequency Encoding
Replace categorical value with its frequency in the training set.
3. Lag Features
For time series: lag-1, lag-7, lag-30 values of the target.
4. Rolling Statistics
Mean, std, min, max over rolling windows.
5. Interaction Terms
Multiply or divide two numerical features that have domain meaning.
6. Date Parts
Extract year, month, day, hour, weekday, quarter, is_weekend.
7. Rank Features
Rank within group — useful for normalizing scale.
8. Aggregation Features
Group by entity (user, card, store) and compute statistics.