Commit the lab into a new selection result

Returns a new scr_result in which the accepted manual entries replace the optimal ones inside fit (the automatic fit is frozen as fit_auto), the screening and hold-out rows of those variables are recomputed with the very same pipeline functions, the final shortlist is the one implied by scr_classing_choose(), and the funnel, gains, SQL and summary are rebuilt with a provenance column. scr_selected() on the result returns the final list (which = "consensus" still gives the automatic one). The ledger travels with the result and into scr_scorecard() and scr_export(). The input result is not modified.

Usage

scr_classing_apply(lab)

Arguments

lab

An object from scr_coarse_classing().

Value

An scr_result with a lab component (ledger, spec, shortlist, source).

See also

scr_coarse_classing() for a complete session, from lab to scorecard.

Other classing: scr_classing_accept(), scr_classing_choose(), scr_classing_propose(), scr_classing_spec(), scr_classing_view(), scr_coarse_classing(), scr_decisions()

Examples

cfg <- scr_config(verbose = FALSE, nthread = 1, use_ranger = FALSE,
                  use_lightgbm = FALSE, xgb_rounds = 40, n_boot = 10)
d <- scr_demo[, c("default", "ref_date", "ds_region", "ds_band", "vl_score_01",
                  "vl_score_02", "vl_score_05", "vl_score_10", "vl_hist_01")]
res <- scr_select(d, "default", config = cfg, date_col = "ref_date")
lab <- scr_coarse_classing(res)
p <- scr_classing_propose(lab, "ds_region",
                          groups = list(edge = c("NORTH", "SOUTH"),
                                        core = c("EAST", "WEST", "CENTRE")))
lab <- scr_classing_accept(lab, p, reason = "edge/core is what pricing uses")
res2 <- scr_classing_apply(lab)
scr_selected(res2)
#> [1] "vl_score_01" "vl_score_02" "ds_band"     "ds_region"   "vl_score_05"
#> [6] "vl_score_10"
scr_decisions(res2)
#>      seq                  at author  variable action proposal_id
#>    <int>              <POSc> <char>    <char> <char>      <char>
#> 1:     1 2026-10-02 00:02:38 runner ds_region accept        P001
#>                                                                      instruction
#>                                                                           <char>
#> 1: groups = list(edge = c("NORTH", "SOUTH"), core = c("EAST", "WEST", "CENTRE"))
#>    n_bins_before n_bins_after iv_train_before iv_train_after iv_holdout_before
#>            <int>        <int>           <num>          <num>             <num>
#> 1:             5            2      0.08464808     0.07392963        0.09714339
#>    iv_holdout_after    psi_after verdict           warnings
#>               <num>        <num>  <char>             <char>
#> 1:       0.07858917 0.0002621977  REVIEW IV_LOSS_VS_OPTIMAL
#>                            reason
#>                            <char>
#> 1: edge/core is what pricing uses