fuel

<p>See mlr_tasks_fuel for a description of the dataset.</p>

datasets

internal

Extends the 'mlr3' ecosystem to functional analysis by adding
support for irregular and regular functional data as defined in the
'tf' package.  The package provides 'PipeOps' for preprocessing
functional columns and for extracting scalar features, thereby
allowing standard machine learning algorithms to be applied
afterwards. Available operations include simple functional features
such as the mean or maximum, smoothing, interpolation, flattening, and
functional 'PCA'.

Sebastian Fischer

mlr3fda

Extending 'mlr3' to Functional Data Analysis

Maximilian Mücke

Fabian Scheipl

Bernd Bischl

fuel function

<p>A data frame with 129 rows and 4 variables</p>

Format

The fuel dataset — fuel

The fuel dataset

fuel: The fuel dataset

Description

Usage

Arguments

Format