mltools (version 0.3.5)

rmsle: Root Mean Square Logarithmic Error

Description

Calculate Root-Mean-Square-Logarithmic Error (Deviation)

For the ith sample, Squared Logarithmic Error is calculated as SLE = (log(prediction + 1) - log(actual + 1))^2. RMSLE is then sqrt(mean(squared logarithmic errors)). Note the '+1' in the calculation of SLE which avoids taking the logarithm of 0 for data which may include 0s.

Usage

rmsle(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-Logarithmic Error (Deviation)

Examples

# NOT RUN {
preds <- c(1.0, 2.0, 9.5)
actuals <- c(0.9, 2.1, 10.0)
rmsle(preds, actuals)

# }