rmse
Computes Root Mean Squared Error between two vectors. It is the average of the amount of mistakes made by regression model in prediction, where the best value is 0 and the worst value tends to infinity (it increases as the deviation between predicted and actual value increases).
Attention: Available only with Activate commercial edition.
Syntax
Score = rmse(targets,predictions)
Inputs
- targets
- Actual label for each observation.
- predictions
- RMSE for each observation.
Outputs
- Score
- Explained variance of the regression model.
Example
Usage of rmse
targets = [3.14, 0.1, 50, -2.5];
predictions = [3.1, 0.5, 50.3, -5];
score = rmse(targets, predictions);> score
score = 1.27491176