mlr3 (version 0.12.0)

as_data_backend.Matrix: Create a Data Backend

Description

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).

Usage

# 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, ...)

Arguments

data

(data.frame()) The input data.frame(). Converted to a data.table::data.table() automatically.

primary_key

(character(1) | integer()) Name of the primary key column, or integer vector of row ids.

dense

(data.frame()). Dense data.

...

(any) Additional arguments passed to the respective DataBackend method.

keep_rownames

(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().

Value

DataBackend.

See Also

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/backends.html

• Package mlr3db to store data out-of-memory.

Other DataBackend: DataBackendDataTable, DataBackendMatrix, DataBackend

Examples

# NOT RUN {
# create a new backend using the penguins data:
as_data_backend(palmerpenguins::penguins)
# }