R: Create a data.frame containing functional features from a...

makeFunctionalData {mlr} | R Documentation

## Create a data.frame containing functional features from a normal data.frame.

### Description

To work with functional features, those features need to be stored as a `matrix` column in the data.frame, so `mlr` can automatically recognize them as functional features. This function allows for an easy conversion from a data.frame with numeric columns to the required format. If the data already contains matrix columns, they are left as-is if not specified otherwise in `fd.features`. See `Examples` for the structure of the generated output.

### Usage

    makeFunctionalData(data, fd.features = NULL, exclude.cols = NULL)

### Arguments

`data` | (data.frame) A data.frame that contains the functional features as numeric columns.
`fd.features` | (list) Named list containing `integer` column indices or `character` column names. Each element defines a functional feature, in the given order of the indices or column names. The name of the list element defines the name of the functional feature. All selected columns have to correspond to numeric data.frame entries. The default is `NULL`, which means all numeric features are considered to be a single functional “fd1”.
`exclude.cols` | (character | integer) Column names or indices to exclude from conversion to functionals, even if they are in included in `fd.features`. Default is not to exclude anything.

### Value

(data.frame).

### Examples

    # data.frame where columns 1:6 and 8:10 belong to a functional feature
    d1 = data.frame(matrix(rnorm(100), nrow = 10), "target" = seq_len(10))
    # Transform to functional data
    d2 = makeFunctionalData(d1, fd.features = list("fd1" = 1:6, "fd2" = 8:10))
    # Create a regression task
    makeRegrTask(data = d2, target = "target")

[Package mlr version 2.16.0 Index]