GifariKemal
e8355b3f62
- Dark mode: class-based theme toggle with localStorage persistence and flash prevention - Trade History (/trades): paginated table, stats cards, equity curve chart with DB API endpoints - Backtest Viewer (/backtests): log parser for 35 backtest results, sidebar + detail + comparison tabs - Model Insights: dashboard card + dialog showing feature importance, regime distribution, training history - Alert/Signal Log (/alerts): signal stats, filterable table with execution tracking - API: 8 new endpoints with psycopg2 DB connection pool - Dark mode sweep across books page, about dialog, and all dashboard components - Architecture docs rewritten with Mermaid diagrams (23 docs) - README and FEATURES.md rewritten bilingual (Indonesian + English) - main_live.py: write model_metrics.json on startup and retrain Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
27 lines
830 B
Python
27 lines
830 B
Python
"""
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ML V2 Package
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==============
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Full ML overhaul with better target variables, enhanced features, and ensemble models.
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Components:
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- ml_v2_target.py: Improved target variables (multi-bar + ATR threshold)
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- ml_v2_feature_eng.py: 23 new features (H1 MTF, continuous SMC, regime, price action)
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- ml_v2_model.py: Multi-model support (XGBoost, LightGBM, ensemble)
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- ml_v2_train.py: Training pipeline with purged walk-forward CV
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- backtest_36_ml_v2.py: Main backtest (configs A/B/C/D/E)
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"""
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from .ml_v2_target import TargetBuilder
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from .ml_v2_feature_eng import MLV2FeatureEngineer
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from .ml_v2_model import TradingModelV2, ModelType
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from .ml_v2_train import ExperimentConfig, MLV2Trainer
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__all__ = [
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"TargetBuilder",
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"MLV2FeatureEngineer",
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"TradingModelV2",
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"ModelType",
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"ExperimentConfig",
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"MLV2Trainer",
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]
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