Synthetic Diabetes Classification Task

A binary classification task for the mlbench::SynthDiabetes2 data set. Positive class is set to "pos". Several feature columns contain missing values, which makes the task useful for preprocessing examples and tests.

The data is fully synthetic and contains no real patient data. It replaces the former pima task, which was based on the PimaIndiansDiabetes2 data set. That data set was removed from mlbench at the request of the institute that conducted the underlying study.

Format

R6::R6Class inheriting from TaskClassif.

Dictionary

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

mlr_tasks$get("diabetes")
tsk("diabetes")

Meta Information

• Task type: “classif”

• Dimensions: 768x9

• Properties: “twoclass”

• Has Missings: TRUE

• Target: “diabetes”

• Features: “age”, “glucose”, “insulin”, “mass”, “pedigree”, “pregnant”, “pressure”, “triceps”

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_sonar, mlr_tasks_spam, mlr_tasks_wine, mlr_tasks_zoo