mlr_learners_classif.JRip: Classification JRip Learner

In henrifnk/mlr3learners.RWeka: AdaBoostM1, IBk ,JRip, J48, LMT, M5Rules, OneR and PART Learner for mlr3

Description

A mlr3::LearnerClassif implementing classification JRip from package RWeka. Calls RWeka::JRip().

Custom mlr3 defaults

• output_debug_info:

  • original id: output-debug-info

• do_not_check_capabilities:

  • original id: do-not-check-capabilities

• num_decimal_places:

  • original id: num-decimal-places

• batch_size:

  • original id: batch-size

• Reason for change: This learner contains changed ids of the following control arguments since their ids contain irregular pattern

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("classif.Jrip")
lrn("classif.Jrip")

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifJRip

Methods

Public methods

• LearnerClassifJRip$new()

• LearnerClassifJRip$clone()

Inherited methods

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifJRip$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifJRip$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Cohen W (1995). Fast effective rule induction In: Proceedings of the 12th International Conference on Machine Learning, pages 115–123. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.50.8204

henrifnk/mlr3learners.RWeka documentation built on June 8, 2020, 5:54 a.m.