MSE: Mean Square Error Loss

In MLmetrics: Machine Learning Evaluation Metrics

Mean Square Error Loss

Description

Compute the mean squared error regression loss.

Usage

MSE(y_pred, y_true)

Arguments

y_pred	Estimated target values vector
y_true	Ground truth (correct) target values vector

Value

Mean Square Error Loss

Examples

data(cars)
reg <- lm(log(dist) ~ log(speed), data = cars)
MSE(y_pred = exp(reg$fitted.values), y_true = cars$dist)

MLmetrics documentation built on May 29, 2024, 9:34 a.m.