more agressive trading avtions. audit
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@ -72,9 +72,9 @@ class TradingOrchestrator:
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self.model_registry = model_registry or get_model_registry()
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self.enhanced_rl_training = enhanced_rl_training
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# Configuration
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self.confidence_threshold = self.config.orchestrator.get('confidence_threshold', 0.20)
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self.confidence_threshold_close = self.config.orchestrator.get('confidence_threshold_close', 0.10)
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# Configuration - AGGRESSIVE for more training data
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self.confidence_threshold = self.config.orchestrator.get('confidence_threshold', 0.15) # Lowered from 0.20
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self.confidence_threshold_close = self.config.orchestrator.get('confidence_threshold_close', 0.08) # Lowered from 0.10
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self.decision_frequency = self.config.orchestrator.get('decision_frequency', 30)
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self.symbols = self.config.get('symbols', ['ETH/USDT', 'BTC/USDT']) # Enhanced to support multiple symbols
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@ -103,7 +103,7 @@ class RealtimeRLCOBTrader:
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trading_executor: TradingExecutor = None,
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model_checkpoint_dir: str = "models/realtime_rl_cob",
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inference_interval_ms: int = 200,
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min_confidence_threshold: float = 0.7,
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min_confidence_threshold: float = 0.35, # Lowered from 0.7 for more aggressive trading
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required_confident_predictions: int = 3):
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self.symbols = symbols or ['BTC/USDT', 'ETH/USDT']
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@ -22,7 +22,7 @@ class TrainingIntegration:
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def __init__(self, orchestrator=None):
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self.orchestrator = orchestrator
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self.training_sessions = {}
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self.min_confidence_threshold = 0.3
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self.min_confidence_threshold = 0.15 # Lowered from 0.3 for more aggressive training
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logger.info("TrainingIntegration initialized")
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