Feature Engineering – The process of creating and selecting informative input variables (features) for a model. In trading, feature engineering involves deriving indicators or statistics from raw price data (for example, moving averages, volatility measures, momentum indicators). Well-engineered features can greatly improve an ML-driven robot’s ability to detect patterns. The quality of features directly affects the model’s performance, accuracy and robustness.

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