Wine data set from the UCI machine learning repository (http://archive.ics.uci.edu/dataset/109/wine). Results of a chemical analysis of three types of wines grown in the same region in Italy but derived from three different cultivars.
Format
R6::R6Class inheriting from TaskClassif.
Source
Original owners: Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pharmaceutical and Food Analysis and Technologies, Via Brigata Salerno, 16147 Genoa, Italy.
Donor: Stefan Aeberhard, email: stefan@coral.cs.jcu.edu.au
Dictionary
This Task can be instantiated via the dictionary mlr_tasks or with the associated sugar function tsk():
Meta Information
Task type: “classif”
Dimensions: 178x14
Properties: “multiclass”
Has Missings:
FALSETarget: “type”
Features: “alcalinity”, “alcohol”, “ash”, “color”, “dilution”, “flavanoids”, “hue”, “magnesium”, “malic”, “nonflavanoids”, “phenols”, “proanthocyanins”, “proline”
References
Dua, Dheeru, Graff, Casey (2017). “UCI Machine Learning Repository.” http://archive.ics.uci.edu/datasets.
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:
Task,
TaskClassif,
TaskRegr,
TaskSupervised,
TaskUnsupervised,
california_housing,
mlr_tasks,
mlr_tasks_breast_cancer,
mlr_tasks_german_credit,
mlr_tasks_iris,
mlr_tasks_mtcars,
mlr_tasks_penguins,
mlr_tasks_pima,
mlr_tasks_sonar,
mlr_tasks_spam,
mlr_tasks_zoo