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Additional parsnip -related options, depending on the
value of type . Arguments to the underlying model's prediction
function cannot be passed here (use the opts argument instead).
Possible arguments are:
-
interval : for type equal to "survival" or "quantile" , should
interval estimates be added, if available? Options are "none"
and "confidence" .
-
level : for type equal to "conf_int" , "pred_int" , or "survival" ,
this is the parameter for the tail area of the intervals
(e.g. confidence level for confidence intervals).
Default value is 0.95 .
-
std_error : for type equal to "conf_int" or "pred_int" , add
the standard error of fit or prediction (on the scale of the
linear predictors). Default value is FALSE .
-
quantile : for type equal to quantile , the quantiles of the
distribution. Default is (1:9)/10 .
-
eval_time : for type equal to "survival" or "hazard" , the
time points at which the survival probability or hazard is estimated.
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