Measure to compare true observed response with predicted response in regression tasks.
Arguments
- truth
(
numeric()
)
True (observed) values. Must have the same length asresponse
.- response
(
numeric()
)
Predicted response values. Must have the same length astruth
.- sample_weights
(
numeric()
)
Vector of non-negative and finite sample weights. Must have the same length astruth
. The vector gets automatically normalized to sum to one. Defaults to equal sample weights.- na_value
(
numeric(1)
)
Value that should be returned if the measure is not defined for the input (as described in the note). Default isNaN
.- ...
(
any
)
Additional arguments. Currently ignored.
Details
The Root Mean Squared Log Error is defined as $$ \sqrt{\frac{1}{n} \sum_{i=1}^n w_i \left( \ln (1 + t_i) - \ln (1 + r_i) \right)^2}, $$ where \(w_i\) are normalized sample weights.
This measure is undefined if any element of \(t\) or \(r\) is less than or equal to \(-1\).