Normalization vs Standardization Normalization: Scale features between 0 & 1 (MinMax Scaler). Standardization: Scale based on standard normal distribution (mean = 0, std = 1) (StandardScaler). Both improve model performance by handling feature scaling. #MachineLearning #AI
Why is Feature Scaling Important? Without scaling, large-value features (like income vs age) dominate models. Needed in: Linear Regression (faster training) KNN, K-Means (distance-based) Deep Learning (stable gradients) Not needed in: Decision Trees Random Forest XGBoost
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