rmse {mltools} | R Documentation |
Root Mean Square Error
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)
[Package mltools version 0.3.5 Index]