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 Percent Bias is defined as $$ \frac{1}{n} \sum_{i=1}^n w_i \frac{\left( t_i - r_i \right)}{\left| t_i \right|}, $$ where \(w_i\) are normalized sample weights. Good predictions score close to 0.
Meta Information
Type:
"regr"
Range: \((-\infty, \infty)\)
Minimize:
NA
Required prediction:
response