mrleo1nidandClaude Opus 5.5 58bd14ef38 feat(recommender): LightGBM lambdarank ranker with impression features (M6) ...

The wave logs each served candidate's feature vector to rec_impression_features.
Nightly training joins them with impression outcomes, validates on the last week
and activates the model only when it beats the v1 order and the active model.
The service loads the active ranker and uses its order in place of the v1 score.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

2026-10-20 22:41:26 +03:00

..

__init__.py

feat(rec): audio analyzer and My Wave v1 engine (M4)

2026-10-20 12:20:55 +03:00

contexts.py

feat(rec): audio analyzer and My Wave v1 engine (M4)

2026-10-20 12:20:55 +03:00

contexts.yaml

feat(rec): audio analyzer and My Wave v1 engine (M4)

2026-10-20 12:20:55 +03:00

engine.py

feat(recommender): LightGBM lambdarank ranker with impression features (M6)

2026-10-20 22:41:26 +03:00

service.py

feat(recommender): LightGBM lambdarank ranker with impression features (M6)

2026-10-20 22:41:26 +03:00

store.py

feat: taste onboarding for new listeners (M6)

2026-10-20 22:35:43 +03:00