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- MLTrainer class with feature matrix builder from top factors by IC - LightGBM training with time-series split (80/20) and early stopping - Feature importance analysis (gain-based) with ranking - Model persistence: model.txt + metadata.json + feature_importance.json + CSV - Feedback generation for factor generation loop - Model loading from disk - Full pipeline: load factors -> train -> save -> generate feedback - 46 unit tests covering all features - lightgbm and scipy added to requirements.txt