mlr_tasks_fuel {mlr3fda}

Fuel Regression Task

Description

This dataset contains two functional covariates and one scalar covariate. The goal is to predict the heat value of some fuel based on the ultraviolet radiation spectrum and infrared ray radiation and one scalar column called h2o.

This is a subset of the full dataset, which is contained in the package FDboost.

Format

R6::R6Class inheriting from mlr3::TaskRegr.

Dictionary

This Task can be instantiated via the dictionary mlr_tasks or with the associated sugar function tsk():

mlr_tasks$get("fuel")
tsk("fuel")

Meta Information

• Task type: “regr”

• Dimensions: 129x4

• Properties: -

• Has Missings: FALSE

• Target: “heatan”

• Features: “NIR”, “UVVIS”, “h20”

References

Brockhaus, Sarah, Scheipl, Fabian, Hothorn, Torsten, Greven, Sonja (2015). “The functional linear array model.” Statistical Modelling, 15(3), 279–300.

See Also

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html

• Package mlr3data for more toy tasks.

• Package mlr3oml for downloading tasks from https://www.openml.org.

• Package mlr3viz for some generic visualizations.

• Dictionary of Tasks: mlr_tasks

• as.data.table(mlr_tasks) for a table of available Tasks in the running session (depending on the loaded packages).

• mlr3fselect and mlr3filters for feature selection and feature filtering.

• Extension packages for additional task types:

  • Unsupervised clustering: mlr3cluster

  • Probabilistic supervised regression and survival analysis: https://mlr3proba.mlr-org.com/.

Other Task: mlr_tasks_dti, mlr_tasks_phoneme