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Regression measure defined as $$ \frac{1}{n} \sum_{i=1}^n \left( t_i - r_i \right). $$ Good predictions score close to 0.
bias(truth, response, ...)
(numeric()) True (observed) values. Must have the same length as response.
numeric()
response
(numeric()) Predicted response values. Must have the same length as truth.
truth
(any) Additional arguments. Currently ignored.
any
Performance value as numeric(1).
numeric(1)
Type: "regr"
"regr"
Range: \((-\infty, \infty)\)
Minimize: NA
NA
Required prediction: response
Other Regression Measures: ktau(), mae(), mape(), maxae(), maxse(), medae(), medse(), mse(), msle(), pbias(), rae(), rmse(), rmsle(), rrse(), rse(), rsq(), sae(), smape(), srho(), sse()
ktau()
mae()
mape()
maxae()
maxse()
medae()
medse()
mse()
msle()
pbias()
rae()
rmse()
rmsle()
rrse()
rse()
rsq()
sae()
smape()
srho()
sse()
# NOT RUN { set.seed(1) truth = 1:10 response = truth + rnorm(10) bias(truth, response) # }
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