mlr_learners_classif.naive_bayes_multinomial: Classification Multinomial Naive Bayes Learner From Weka

mlr_learners_classif.naive_bayes_multinomialR Documentation

Classification Multinomial Naive Bayes Learner From Weka

Description

Multinomial Naive Bayes classifier. Calls RWeka::make_Weka_classifier() from RWeka.

Custom mlr3 parameters

  • 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

Dictionary

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

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

Meta Information

  • Task type: “classif”

  • Predict Types: “response”, “prob”

  • Feature Types: “integer”, “numeric”

  • Required Packages: mlr3, RWeka

Parameters

Id Type Default Levels Range
subset untyped - -
na.action untyped - -
output_debug_info logical FALSE TRUE, FALSE -
do_not_check_capabilities logical FALSE TRUE, FALSE -
num_decimal_places integer 2 [1, \infty)
batch_size integer 100 [1, \infty)
options untyped NULL -

Super classes

mlr3::Learner -> mlr3::LearnerClassif -> LearnerClassifNaiveBayesMultinomial

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
LearnerClassifNaiveBayesMultinomial$new()

Method clone()

The objects of this class are cloneable with this method.

Usage
LearnerClassifNaiveBayesMultinomial$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Author(s)

damirpolat

References

Mccallum A, Nigam K (1998). “A Comparison of Event Models for Naive Bayes Text Classification.” In AAAI-98 Workshop on 'Learning for Text Categorization'.

See Also

Examples

learner = mlr3::lrn("classif.naive_bayes_multinomial")
print(learner)

# available parameters:
learner$param_set$ids()

mlr-org/mlr3extralearners documentation built on April 13, 2024, 5:25 a.m.