nmse {kerntools} | R Documentation |
NMSE (Normalized Mean Squared Error)
Description
'nmse()' computes the Normalized Mean Squared Error between the output of a regression model and the actual values of the target.
Usage
nmse(target, pred)
Arguments
target |
Numeric vector containing the actual values. |
pred |
Numeric vector containing the predicted values. (The order should be the same than in the target) |
Details
The Normalized Mean Squared error is defined as:
NMSE=MSE/((N-1)*var(target))
where MSE is the Mean Squared Error.
Value
The normalized mean squared error (a single value).
Examples
y <- 1:10
y_pred <- y+rnorm(10)
nmse(y,y_pred)
[Package kerntools version 1.0.2 Index]