survex
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Published
20 hours ago •
ModelOriented
ModelOriented
Error message encountered with mlr3 parametric learner
Hi survex team,
I encountered the following error message "Error in vecdist$wrappedModels()[[i]]: wrong arguments for subsetting an environment" when applying model_survshap function with aft_weibull model from mlr3. This has not been a problem with other models/learners from mlr3 in my experience.
Any insight and suggestion on how this may be debugged would be very much appreciated!
library(mlr3)
library(mlr3extralearners)
library(mlr3pipelines)
library('mlr3proba')
library(survival)
library(survex)
lung = tsk('lung')$data()
aft=lrn('surv.parametric')
aft$train(tsk('lung'))
class(aft) = c(class(aft), 'LearnerSurv')
aft_exp_lung = explain(aft,
data= lung[, -c(1,2)],
y=Surv(lung$time, lung$status),
label = 'aft')
#> Preparation of a new explainer is initiated
#> -> model label : aft
#> -> data : 168 rows 7 cols
#> -> target variable : 168 values ( 121 events and 47 censored )
#> -> times : 50 unique time points , min = 8 , median survival time = 320 , max = 918
#> -> times : ( generated from y as uniformly distributed survival quantiles based on Kaplan-Meier estimator )
#> -> predict function : predict_newdata()$crank will be used ( [33m default [39m )
#> -> predict survival function : predict_newdata()$distr$survival will be used ( [33m default [39m )
#> -> predict cumulative hazard function : predict_newdata()$distr$cumHazard will be used ( [33m default [39m )
#> -> model_info : package mlr3proba , ver. 0.6.3 , task survival ( [33m default [39m )
#> A new explainer has been created!
kernelSHAP_aft_lung = model_survshap(explainer = aft_exp_lung,
calculation_method = 'kernelshap',
aggregation_method = 'integral',
output_type = 'risk')
#> Error in vecdist$wrappedModels()[[i]]: wrong arguments for subsetting an environment
Created on 2024-09-19 by the reprex package (v2.0.1)
Session info
sessioninfo::session_info()
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