Information
- NRMSE (Normalized Root Mean Squared Error) is a measure of the accuracy of a regression model, representing the ratio of the root mean squared error to the range of the dependent variable.
- It is used to compare the performance of different models or to evaluate the accuracy of a model over time.
- The formula for NRMSE is: NRMSE = RMSE / (y_max - y_min), where RMSE is the root mean squared error, and y_max and y_min are the maximum and minimum values of the dependent variable, respectively.
- NRMSE values range from 0 to 1, with lower values indicating better model accuracy.
- NRMSE can be used to determine the relative performance of different models or to evaluate the performance of a single model over time by comparing its NRMSE values across different time periods.
'Zettelkasten > Terminology Information' 카테고리의 다른 글
| DA (Domain Adaptation) (0) | 2023.03.18 |
|---|---|
| CNN (Convolutional Neural Network) (0) | 2023.03.17 |
| LSTM (Long Short-Term Memory) (0) | 2023.03.16 |
| Multi-step ahead forecasting (0) | 2023.03.15 |
| Ensemble learning (0) | 2023.03.15 |
댓글