rmse: Root Mean Square Error

In ben519/mltools: Machine Learning Tools

Description

Calculate Root-Mean-Square Error (Deviation)

For the ith sample, Squared Error is calculated as SE = (prediction - actual)^2. RMSE is then sqrt(mean(squared errors)).

Usage

rmse(preds = NULL, actuals = NULL, weights = 1, na.rm = FALSE)

Arguments

preds	A vector of prediction values in [0, 1]
actuals	A vector of actuals values in 0, 1, or FALSE, TRUE
weights	Optional vectors of weights
na.rm	Should (prediction, actual) pairs with at least one NA value be ignored?

Details

Calculate Root-Mean-Square Error (Deviation)

References

https://en.wikipedia.org/wiki/Root-mean-square_deviation

Examples

preds <- c(1.0, 2.0, 9.5)
actuals <- c(0.9, 2.1, 10.0)
rmse(preds, actuals)

ben519/mltools documentation built on Sept. 22, 2021, 4:30 p.m.