Advanced Multilabel Classification Recipes
Predict multiple independent outcomes per entity — with time-of-day filtering, rolling weekly windows, and multi-channel detection.
Common advanced patterns
- Time-of-day filtering — extract hours from timestamps to filter events by time slot (e.g., evening only)
- Rolling window iteration — evaluate conditions across multiple consecutive time windows (e.g., week-by-week)
- Multi-channel detection — track escalation or activity across multiple parallel channels using extra columns
Ready-to-run solutions
| Recipe | Industry | Advanced Pattern |
|---|---|---|
| Evening Brand Purchases | Retail | Hour extraction, time-of-day filter |
| Weekly Category Purchases | Retail | Rolling 12-week windows, stacked arrays |
| Ticket Escalation Channels | Support | Multi-channel extra columns, pandas variation |
See also
For simpler multilabel classification examples, see the basic Multilabel Classification recipes.