Classification C5.0 Learner
mlr_learners_classif.C50.Rd
Decision Tree Algorithm.
Calls C50::C5.0.formula()
from C50.
Dictionary
This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn()
:
$get("classif.C50")
mlr_learnerslrn("classif.C50")
Meta Information
Task type: “classif”
Predict Types: “response”, “prob”
Feature Types: “numeric”, “factor”, “ordered”
Required Packages: mlr3, mlr3extralearners, C50
Parameters
Id | Type | Default | Levels | Range |
trials | integer | 1 | \([1, \infty)\) | |
rules | logical | FALSE | TRUE, FALSE | - |
costs | untyped | - | ||
subset | logical | TRUE | TRUE, FALSE | - |
bands | integer | - | \([0, 1000]\) | |
winnow | logical | FALSE | TRUE, FALSE | - |
noGlobalPruning | logical | FALSE | TRUE, FALSE | - |
CF | numeric | 0.25 | \([0, 1]\) | |
minCases | integer | 2 | \([0, \infty)\) | |
fuzzyThreshold | logical | FALSE | TRUE, FALSE | - |
sample | numeric | 0 | \([0, 0.999]\) | |
seed | integer | - | \((-\infty, \infty)\) | |
earlyStopping | logical | TRUE | TRUE, FALSE | - |
label | untyped | outcome | - | |
na.action | untyped | stats::na.pass | - |
Super classes
mlr3::Learner
-> mlr3::LearnerClassif
-> LearnerClassifC50