nmse: NMSE (Normalized Mean Squared Error)

In kerntools: Kernel Functions and Tools for Machine Learning Applications

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)

kerntools documentation built on April 3, 2025, 7:52 p.m.