Rule-Based Systems
Machine Learning
The square root of the mean squared error, providing an error metric in the same units as the target variable.
Detailed Explanation
Root Mean Squared Error (RMSE) is a widely used metric to evaluate the accuracy of regression models. It calculates the square root of the average squared differences between predicted and actual values, providing an error measure in the same units as the target variable. Lower RMSE indicates better model performance and more accurate predictions.
Use Cases
- •RMSE is used to compare the accuracy of different regression models on housing price prediction.
Related Terms
Other terms in the Machine Learning category