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List Learners in mlr3verse

list_mlr3learners.Rd

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

Usage

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