as_data_backend.Matrix {mlr3}

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 class 'Matrix'
as_data_backend(data, primary_key = NULL, dense = NULL, ...)

as_data_backend(data, primary_key = NULL, ...)

## S3 method for class 'data.frame'
as_data_backend(data, primary_key = NULL, keep_rownames = FALSE, ...)

Arguments

data

(data.frame())
The input data.frame(). Automatically converted to a data.table::data.table().

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/chapters/chapter10/advanced_technical_aspects_of_mlr3.html#sec-backends

• Package mlr3db to interface out-of-memory data, e.g. SQL servers or duckdb.

Other DataBackend: DataBackend, DataBackendDataTable, DataBackendMatrix

Examples

# create a new backend using the penguins data:
as_data_backend(palmerpenguins::penguins)