se: Squared Error

In Metrics: Evaluation Metrics for Machine Learning

Description

se computes the elementwise squared difference between two numeric vectors.

Usage

se(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

mse rmse

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)
se(actual, predicted)

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