Evaluation Metrics: RMSE

 Evaluation Metrics: RMSE

Evaluation metrics are essential tools for assessing the performance of machine learning models, particularly in regression tasks where you're predicting continuous values. Here are descriptions of three common evaluation metrics: Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2).

Root Mean Square Error (RMSE):

RMSE is similar to MAE but emphasizes the squared differences between predicted and actual values, which gives higher weight to larger errors.