mlr_learners_regr.M5Rules: Regression M5Rules Learner

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

Description

A mlr3::LearnerRegr implementing classification JRip from package RWeka. Calls RWeka::M5Rules().

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("regr.M5Rules")
lrn("regr.M5Rules")

Super classes

mlr3::Learner -> mlr3::LearnerRegr -> LearnerRegrM5Rules

Methods

Public methods

• LearnerRegrM5Rules$new()

• LearnerRegrM5Rules$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

LearnerRegrM5Rules$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerRegrM5Rules$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Hall M, Et al. (1999) Generating rule sets from model trees In: Proceedings of the Twelfth Australian Joint Conference on Artificial Intelligence, pages 1- 12. http://citeseer.ist.psu.edu/holmes99generating.html

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