Propose manual bins for a variable

Exactly one of breaks, groups, merge, split or reset per call; missing_to and other_to compose with a categorical instruction. The instruction is resolved against the current bins into an absolute specification, the WOE is refitted on the training rows, the bins are applied frozen to the hold-out, and the comparison against the optimal bins is printed. The proposal is a value: nothing changes in the lab until scr_classing_accept().

Usage

scr_classing_propose(
  lab,
  variable,
  breaks = NULL,
  groups = NULL,
  merge = NULL,
  split = NULL,
  missing_to = NULL,
  other_to = NULL,
  reset = FALSE
)

Arguments

lab

An object from scr_coarse_classing().

variable

A variable of the lab.

breaks

Numeric: interior cut points, (-Inf, b1], (b1, b2], ....

groups

Categorical: a list of character vectors, one per bin; names are display labels. Every training category must be assigned, or other_to must name the catch-all bin.

merge

Bin ids to merge (adjacent for numerics).

split

c(id, at): split numeric bin id at at.

missing_to

Categorical: fold the "MISSING" category into this bin.

other_to

Categorical: the bin that receives every training category not listed in groups.

reset

TRUE proposes a return to the optimal bins.

Value

An scr_classing_proposal with id, variable, instruction (the resolved instruction as text), entry (the hand-built bins), checks, optimal (the checks of the optimal bins), compare, verdict (ACCEPTABLE, REVIEW or BLOCKED), warnings and blocking.

See also

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

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