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Rmse Mse Linear Regression

src/data/question-groups/data-science/content/rmse-mse-linear-regression.md

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To evaluate a regression model:

python
from sklearn.metrics import mean_squared_error  
import numpy as np  
mse = mean_squared_error(y_true, y_pred)  
rmse = np.sqrt(mse)
  • MSE: Penalizes large errors heavily.
  • RMSE: More interpretable because it's in the same unit as the target.

Another alternative:

python
from sklearn.metrics import mean_absolute_error
mae = mean_absolute_error(y_true, y_pred)

MAE is less sensitive to outliers.