sse: Sum of Squared Errors

In Metrics: Evaluation Metrics for Machine Learning

Description

sse computes the sum of the squared differences between two numeric vectors.

Usage

sse(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

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)
sse(actual, predicted)

Example output

[1] 0.67

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