#CurrencyPairPrediction Feature Selection Not all features help. Some are noisy or redundant. Techniques: • Correlation Analysis: Drop highly correlated features to avoid multicollinearity. • Feature Importance Scores: Use models like Random Forests or XGBoost to rank features. • Recursive Feature Elimination (RFE): Iteratively remove less important features. • PCA (Principal Component Analysis): Reduce feature dimensionality while preserving most variance.