Wraps a DataBackend around data.
mlr3 ships with methods for data.frame (converted to a DataBackendDataTable
and Matrix from package Matrix (converted to a DataBackendMatrix).
Additional methods are implemented in the package mlr3db, e.g. to connect to real DBMS like PostgreSQL (via dbplyr) or DuckDB (via DBI/duckdb).
# S3 method for Matrix
as_data_backend(data, primary_key = NULL, dense = NULL, ...)as_data_backend(data, primary_key = NULL, ...)
# S3 method for data.frame
as_data_backend(data, primary_key = NULL, keep_rownames = FALSE, ...)
DataBackend.
(data.frame())
The input data.frame().
Automatically converted to a data.table::data.table().
(character(1) | integer())
Name of the primary key column, or integer vector of row ids.
(data.frame()).
Dense data.
(any)
Additional arguments passed to the respective DataBackend method.
(logical(1) | character(1))
If TRUE or a single string, keeps the row names of data as a new column.
The column is named like the provided string, defaulting to "..rownames" for keep_rownames == TRUE.
Note that the created column will be used as a regular feature by the task unless you manually change the column role.
Also see data.table::as.data.table().
Chapter in the mlr3book: https://mlr3book.mlr-org.com/technical.html#backends
Package mlr3db to interface out-of-memory data, e.g. SQL servers or duckdb.
Other DataBackend:
DataBackendDataTable,
DataBackendMatrix,
DataBackend
# create a new backend using the penguins data:
as_data_backend(palmerpenguins::penguins)
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