Dataset readiness · LIVE
80Historical signals
77Stocks represented
0Rows usable for first success model
0Rows usable for false-breakout model
0Rows with 20-session return
100.0%Historical RS coverage
Too small for a serious model
The first XGBoost classifier uses only resolved triggered outcomes:
TARGET = 1, STOP/TIMEOUT = 0. PENDING, AMBIGUOUS and NOT_TRIGGERED are excluded.
NIFTY 500 historical breadth table detected. Breadth columns are exported with a
membership-quality flag. Approximate historical membership is not silently treated as pristine data.
What happens next
1. Complete Phase 1B historical RS / breadth enrichment
2. Export ML Dataset v1B CSV
3. Train Logistic Regression baseline
4. Train XGBoost classifier on the same chronological split
5. Compare ROC-AUC, PR-AUC, Brier score, precision and top-decile performance
6. Save model + feature importance
7. Only if XGBoost beats the baseline → integrate predictions into OmmAlpha