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Attach a Saved Model to Fresh Data

Source: R/il_model.R
il_attach.Rd

Takes a loaded (or existing) il_model and binds it to new data and a fresh database connection, producing a model ready for predict() or further training. Accepts in-memory data frames, dbplyr::tbl_lazy table references, or character table names.

Usage

il_attach(model, .data, ..., con = NULL, link_type = NULL)

Arguments

model

An il_model object, typically from il_load().

.data

A data frame, tibble::tibble(), dbplyr::tbl_lazy, or character table name. The first (or only) input dataset.

...

Additional datasets for multi-table linkage.

con

A DBI connection object from DBI::dbConnect(). Optional when .data is a dbplyr::tbl_lazy, the connection is extracted from the table reference.

Optionally override the model's link type. If NULL (default), uses the link type stored in the model.

Value

The model, now connected to con with data uploaded, ready for predict(), il_find_matches(), or further training.

Details

This is the key function for the production workflow: train once with il_model() -> save with il_save() -> later, load with il_load() and attach to new data with il_attach().

The loaded model's trained parameters (m, u, prior) are preserved. You can immediately call predict() on the attached model, or continue training with il_estimate_em() using the existing parameters as a warm start.

Examples

con <- DBI::dbConnect(duckdb::duckdb())
spec <- il_spec() |>
  il_compare(first_name, cl_jaro_winkler(0.9, 0.7)) |>
  il_block_on(surname)
model <- il_model(fake_1000, spec = spec, con = con)
model <- il_estimate_u(model)
model <- il_estimate_em(model, block_on(surname))
#> EM trained: first_name
path <- tempfile(fileext = '.rds')
il_save(model, path)
DBI::dbDisconnect(con, shutdown = TRUE)
con2 <- DBI::dbConnect(duckdb::duckdb())
loaded <- il_load(path)
model2 <- il_attach(loaded, fake_1000, con = con2)
DBI::dbDisconnect(con2, shutdown = TRUE)