Returns a tidy tibble of parameter estimates at each EM iteration,
useful for diagnosing convergence. Designed for use with
ggplot2::geom_line() and ggplot2::facet_wrap().
Value
A tibble::tibble() with columns session, iteration, comparison,
gamma_level, and value.
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_training_history(model)
#> # A tibble: 104 × 5
#> session iteration comparison gamma_level value
#> <int> <int> <chr> <int> <dbl>
#> 1 1 1 first_name 0 0.143
#> 2 1 1 first_name 1 0.162
#> 3 1 1 first_name 2 0.695
#> 4 1 1 surname 0 0.05
#> 5 1 1 surname 1 0.05
#> 6 1 1 surname 2 0.9
#> 7 1 1 dob 0 0.217
#> 8 1 1 dob 1 0.783
#> 9 1 2 first_name 0 0.0177
#> 10 1 2 first_name 1 0.193
#> # ℹ 94 more rows
DBI::dbDisconnect(con, shutdown = TRUE)