Lists all learners, properties, and associated packages in a table that can be filtered and queried.

list_mlr3learners(select = NULL, filter = NULL)

Arguments

select

character()
Passed to data.table::subset.

filter

list()
Named list of conditions to filter on, names correspond to column names in table.

Examples

list_mlr3learners( select = c("id", "properties", "predict_types"), filter = list(class = "surv", predict_types = "distr"))
#> id properties #> 1: surv.akritas #> 2: surv.blackboost weights #> 3: surv.cforest weights #> 4: surv.coxboost weights #> 5: surv.coxph weights #> 6: surv.coxtime #> 7: surv.ctree weights #> 8: surv.cv_coxboost weights #> 9: surv.deephit #> 10: surv.deepsurv #> 11: surv.dnnsurv #> 12: surv.flexible weights #> 13: surv.gamboost importance,selected_features,weights #> 14: surv.glmboost weights #> 15: surv.kaplan missings #> 16: surv.loghaz #> 17: surv.mboost importance,selected_features,weights #> 18: surv.nelson missings #> 19: surv.obliqueRSF missings,oob_error #> 20: surv.parametric weights #> 21: surv.pchazard #> 22: surv.penalized #> 23: surv.ranger importance,oob_error,weights #> 24: surv.rfsrc importance,missings,oob_error,weights #> 25: surv.rpart importance,missings,selected_features,weights #> id properties #> predict_types #> 1: crank,distr #> 2: distr,crank,lp #> 3: distr,crank #> 4: distr,crank,lp #> 5: distr,crank,lp #> 6: crank,distr #> 7: distr,crank #> 8: distr,crank,lp #> 9: crank,distr #> 10: crank,distr #> 11: crank,distr #> 12: distr,crank,lp #> 13: distr,crank,lp #> 14: distr,crank,lp #> 15: crank,distr #> 16: crank,distr #> 17: distr,crank,lp #> 18: crank,distr #> 19: crank,distr #> 20: distr,lp,crank #> 21: crank,distr #> 22: distr,crank #> 23: distr,crank #> 24: crank,distr #> 25: crank,distr #> predict_types