# 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).

## Syntax

Score = rmse(targets,predictions)

## Inputs

targets
Actual label for each observation.
Type: double
Dimension: vector
predictions
RMSE for each observation.
Type: double
Dimension: vector

## Outputs

Score
Explained variance of the regression model.
Type: double
Dimension: scalar

## 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