Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

msle

Mean Squared Log Error


Description

msle computes the average of squared log error between two numeric vectors.

Usage

msle(actual, predicted)

Arguments

actual

The ground truth non-negative vector

predicted

The predicted non-negative vector, where each element in the vector is a prediction for the corresponding element in actual.

Details

msle adds one to both actual and predicted before taking the natural logarithm to avoid taking the natural log of zero. As a result, the function can be used if actual or predicted have zero-valued elements. But this function is not appropriate if either are negative valued.

See Also

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)
msle(actual, predicted)

Metrics

Evaluation Metrics for Machine Learning

v0.1.4
BSD_3_clause + file LICENSE
Authors
Ben Hamner [aut, cph], Michael Frasco [aut, cre], Erin LeDell [ctb]
Initial release

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.