BizzleBot 4647c596b3 feat: ML-optimized accumulation scoring with dashboard toggle ...

Train GradientBoostedClassifier on 2,601 days of historical data
(2018-2025) to find optimal metric weights for identifying the best
long-term buying opportunities. Uses time-series cross-validation
to prevent look-ahead bias.

Key results:
- pct_above_200w_sma: 50.7% weight (was 11.1% equal)
- drawdown: 14.6%, lth_rp: 10.9%, rhodl: 8.9%
- fear_greed demoted from 11.1% to 5.1%
- nupl/mvrv nearly eliminated (0.7-1.8%)

ML Strong Accumulation bracket: avg +210% 1yr (vs +176% classic)

New files: ml/optimizer.py, config/ml_weights.json
Modified: scoring/engine.py (score_all_ml), backtesting/engine.py
(ml_mode), dashboard/server.py (Classic/ML toggle)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-21 23:18:29 +00:00

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