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Fit a false-positive filter on labelled match pairs

Source: R/calibration_filter.R
fit_filter.Rd

Fit a baseline classifier to predict whether each scored pair is a true match (equal == 1L) or a false positive (equal == 0L). The baseline path uses stats::glm with the logit link and no external dependencies. The features object is the input from match_features(); labels carry the equal column produced by import_labels().

Usage

fit_filter(
  features,
  labels,
  model = "logistic",
  class_weighted = FALSE,
  na_fill = 0,
  ...
)

Arguments

features

A Match_Features object.

labels

A data.table / data.frame with the matches schema plus an integer equal column (0L / 1L). Typically produced by import_labels().

model

Character scalar (default "logistic") selecting the baseline glm() path. Future M6 work will accept a fitted parsnip / workflow object here.

class_weighted

Logical scalar. When TRUE, fit glm with inverse-class-frequency weights =, useful for imbalanced training sets. Default FALSE.

na_fill

Numeric scalar used to impute predictor NAs. Default 0 (sensible for aIP slot columns where NA means "no token").

...

Reserved for future expansion.

Value

A Filter_Model object.

Examples

strat <- search_strategy(
  workshop   ~ normalize_text() + word_tokens(min_nchar = 3),
  proprietor ~ normalize_text() + word_tokens(min_nchar = 2),
  block_by  = c("postcode_area", "trade"),
  threshold = 0.30
)
matches <- search_candidates(
  workshop_listings, workshop_register,
  base_id = "listing_id", target_id = "reg_no", strategy = strat
)
feats <- match_features(matches, strat,
                        base = workshop_listings, id = "listing_id",
                        target = workshop_register, target_id = "reg_no")
# match_labels_example carries the same pairs with a hand-checked `equal` flag.
model <- fit_filter(feats, match_labels_example)
model
#> <joinery::Filter_Model>
#> backend : glm
#> model_class : glm
#> predictors (42) : score, cnt, icnt, ipos, scnt, rcnt, r1, r2
#> ... +34 more
#> training_n : 442
#> class_balance : 0.756 (share of equal == 1L)
#> class_weighted : FALSE