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@@ -59,7 +59,6 @@ To develop a carbon footprint detection system that:
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  ### Why Random Forest Regressor?
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- RandomForestRegressor was chosen because:
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  - It handles non-linear relationships and interactions between features better than linear models.
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  - It’s robust to overfitting due to its ensemble nature.
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  - Outperformed linear models in testing, giving: Higher R² and Lower RMSE
 
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  ### Why Random Forest Regressor?
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  - It handles non-linear relationships and interactions between features better than linear models.
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  - It’s robust to overfitting due to its ensemble nature.
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  - Outperformed linear models in testing, giving: Higher R² and Lower RMSE