Returns a tidy tibble of comparison levels with their m probabilities,
u probabilities, and log-2 Bayes factors (match weights). Designed for
use with ggplot2::geom_col() and ggplot2::facet_wrap().
Value
A tibble::tibble() with columns comparison, gamma_level, m_prob,
u_prob, and weight.
Examples
df <- data.frame(
unique_id = 1:20,
first_name = c(
'John', 'Jon', 'Jane', 'Jane', 'Bob',
'Bobby', 'Alice', 'Alicia', 'Tom', 'Thomas',
'John', 'Jon', 'Jane', 'Janet', 'Bob',
'Robert', 'Alice', 'Alison', 'Tom', 'Tomas'
),
surname = c(
'Smith', 'Smith', 'Doe', 'Doe', 'Jones',
'Jones', 'Brown', 'Brown', 'White', 'White',
'Smith', 'Smyth', 'Doe', 'Doe', 'Jones',
'Jones', 'Brown', 'Browne', 'White', 'White'
),
dob = c(
'1990-01-01', '1990-01-01', '1985-06-15', '1985-06-15',
'2000-12-01', '2000-12-01', '1975-03-22', '1975-03-22',
'1988-07-04', '1988-07-04', '1990-01-01', '1990-01-02',
'1985-06-15', '1985-06-16', '2000-12-01', '2000-12-02',
'1975-03-22', '1975-03-23', '1988-07-04', '1988-07-05'
),
city = c(
'London', 'London', 'Paris', 'Paris', 'Berlin',
'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid',
'London', 'London', 'Paris', 'Paris', 'Berlin',
'Berlin', 'Rome', 'Rome', 'Madrid', 'Madrid'
),
email = c(
'john@example.com', 'jon@example.com', 'jane@example.com',
'jane@example.com', 'bob@example.com', 'bobby@example.com',
'alice@example.com', 'alicia@example.com', 'tom@example.com',
'thomas@example.com', 'john@example.com', 'jon@example.com',
'jane@example.com', 'janet@example.com', 'bob@example.com',
'robert@example.com', 'alice@example.com', 'alison@example.com',
'tom@example.com', 'tomas@example.com'
)
)
con <- DBI::dbConnect(duckdb::duckdb())
spec <- il_spec() |>
il_compare(first_name, cl_jaro_winkler(0.9, 0.7)) |>
il_compare(surname, cl_jaro_winkler(0.9, 0.7)) |>
il_compare(dob, cl_exact()) |>
il_block_on(surname) |>
il_block_on(first_name)
model <- il_model(df, spec = spec, con = con)
model <- il_estimate_u(model)
model <- il_estimate_em(model, block_on(surname))
#> EM trained: first_name and dob | skipped (blocked on): surname
il_weights(model)
#> # A tibble: 8 × 5
#> comparison gamma_level m_prob u_prob weight
#> <chr> <int> <dbl> <dbl> <dbl>
#> 1 first_name 0 0.0114 0.832 -6.18
#> 2 first_name 1 0.196 0.0632 1.63
#> 3 first_name 2 0.792 0.105 2.91
#> 4 surname 0 0.05 0.821 -4.04
#> 5 surname 1 0.05 0.0368 0.441
#> 6 surname 2 0.9 0.142 2.66
#> 7 dob 0 0.280 0.921 -1.72
#> 8 dob 1 0.720 0.0789 3.19
DBI::dbDisconnect(con, shutdown = TRUE)