a21e635d9f
Major upgrade to the ML engine: - LSTM model type: 2-layer PyTorch LSTM with early stopping, GPU support - Hybrid mode: LSTM (60%) + XGBoost (40%) with agreement gating - StandardScaler normalization (critical for LSTM) - PCA dimensionality reduction (configurable variance retention) - ATR-based dynamic stop-loss/take-profit adapting to volatility - Rolling window retraining for more realistic time series validation - Updated LLM system prompt with docs for all new parameters - All backward compatible (xgboost/lightgbm/catboost still work) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
63 lines
1.7 KiB
JSON
63 lines
1.7 KiB
JSON
{
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"model_type": "hybrid",
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"features": {
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"technical_indicators": ["RSI_14", "RSI_7", "MACD_line", "MACD_signal", "MACD_hist", "BB_upper", "BB_lower", "BB_width", "ATR_14", "SMA_20", "SMA_50", "EMA_10", "EMA_20", "OBV", "stoch_k", "stoch_d", "williams_r", "CCI_20", "ROC_10"],
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"lookback_periods": [3, 5, 10, 20],
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"use_volume_features": true,
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"use_volatility_features": true,
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"use_candle_patterns": false,
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"use_lag_features": true,
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"lag_periods": [1, 2, 3, 5],
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"use_pca": true,
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"pca_variance": 0.95,
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"use_scaler": true
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},
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"target": {
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"type": "classification",
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"direction": "both",
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"horizon_candles": 8,
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"threshold_pct": 1.5
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},
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"hyperparameters": {
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"learning_rate": 0.001,
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"max_depth": 5,
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"n_estimators": 300,
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"subsample": 0.8,
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"colsample_bytree": 0.8,
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"min_child_weight": 5,
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"gamma": 0.3,
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"reg_alpha": 0.1,
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"reg_lambda": 2.0,
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"lstm_hidden_size": 128,
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"lstm_num_layers": 2,
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"lstm_dropout": 0.3,
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"lstm_epochs": 100,
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"lstm_batch_size": 64,
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"lstm_sequence_length": 20,
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"lstm_patience": 10
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},
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"strategy": {
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"entry_threshold": 0.60,
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"exit_type": "trailing_stop",
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"stop_loss_pct": 2.0,
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"take_profit_pct": 4.0,
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"trailing_stop_pct": 1.5,
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"position_sizing": "confidence_scaled",
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"max_position_pct": 100,
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"min_confidence_to_trade": 0.55,
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"dynamic_sl_tp": true,
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"atr_sl_multiplier": 1.5,
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"atr_tp_multiplier": 3.0
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},
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"training": {
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"walk_forward_windows": 5,
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"train_pct": 0.7,
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"validation_pct": 0.15,
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"test_pct": 0.15,
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"rolling_window": true,
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"rolling_train_size": 2000,
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"rolling_test_size": 200
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},
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"timeframe": "4h"
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}
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