mlr_learners_classif.nnet: Classification nnet Learner

In henrifnk/mlr3learners.nnet: Learner from nnet package for mlr3

Description

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

Custom mlr3 defaults

• size:

  • Adjusted default: 3L

  • Reason for change: has no default in nnet().

Dictionary

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

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

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifNnet

Methods

Public methods

• LearnerClassifNnet$new()

• LearnerClassifNnet$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()

---

Method new()

Creates a new instance of this R6 class.

Usage

LearnerClassifNnet$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerClassifNnet$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Ripley, B (1996). Pattern Recognition and Neural Networks. Cambridge. http://www.stats.ox.ac.uk/~ripley/PRbook/Compl.pdf

henrifnk/mlr3learners.nnet documentation built on June 10, 2020, 3:44 a.m.