mse: Mean Squared Error

In Metrics: Evaluation Metrics for Machine Learning

Description

mse computes the average squared difference between two numeric vectors.

Usage

mse(actual, predicted)

Arguments

actual	The ground truth numeric vector.
predicted	The predicted numeric vector, where each element in the vector is a prediction for the corresponding element in actual.

See Also

rmse mae

Examples

actual <- c(1.1, 1.9, 3.0, 4.4, 5.0, 5.6)
predicted <- c(0.9, 1.8, 2.5, 4.5, 5.0, 6.2)
mse(actual, predicted)

Example output

[1] 0.1116667

Metrics documentation built on May 1, 2019, 10:11 p.m.