Summarise a Match Result

Post-match overview (Q2). Auto-detects whether the input is a duplicate table (presence of duplicate_group column) or a candidate table (presence of match_id and source columns), and reports score distribution, coverage (when base / target are supplied), cluster-size or candidates-per-record distribution, and top-1-vs-top-2 score-gap distribution for candidates. Recommendations link symptoms to strategy levers.

Usage

summarise_matches(matches, ...)

Arguments

matches

Match output table from detect_duplicates() or search_candidates().

...

Method-specific arguments. The data.table method accepts: base (optional base input table for coverage), target (optional target input table for candidate coverage), and bins (integer number of histogram bins for the score distribution; default 50).

Value

A Match_Overview object.

Examples

s <- search_strategy(
  Nachname ~ normalize_text() + word_tokens(min_nchar = 3),
  block_by = "Kreis",
  threshold = 0.8
)
dups <- detect_duplicates(base_example, "id_base", s)
summarise_matches(dups, base = base_example)
#> 
#> ── Match_Overview (duplicates) ─────────────────────────────────────────────────
#> n_pairs_or_groups: "642" n_records_involved: "2935"
#> coverage: base=88.9% target=NA
#> score summary
#> min: 1.000
#> q1: 1.000
#> median: 1.000
#> mean: 1.000
#> q3: 1.000
#> max: 1.000
#> cluster size distribution (top 5)
#> size 2: 208 cluster(s)
#> size 3: 147 cluster(s)
#> size 4: 87 cluster(s)
#> size 5: 50 cluster(s)
#> size 6: 32 cluster(s)