se {mlr3measures} | R Documentation |
Squared Error (per observation)
Description
Measure to compare true observed response with predicted response in regression tasks.
Note that this is an unaggregated measure, returning the losses per observation.
Usage
se(truth, response, ...)
Arguments
truth |
( |
response |
( |
... |
( |
Details
Calculates the per-observation squared error as
\left( t_i - r_i \right)^2.
Value
Performance value as numeric(length(truth))
.
Meta Information
Type:
"regr"
Range (per observation):
[0, \infty)
Minimize (per observation):
TRUE
Required prediction:
response
See Also
Other Regression Measures:
ae()
,
ape()
,
bias()
,
ktau()
,
linex()
,
mae()
,
mape()
,
maxae()
,
maxse()
,
medae()
,
medse()
,
mse()
,
msle()
,
pbias()
,
pinball()
,
rae()
,
rmse()
,
rmsle()
,
rrse()
,
rse()
,
rsq()
,
sae()
,
sle()
,
smape()
,
srho()
,
sse()