DWFuzzyGammaNaiveBayesModel: Double Weighted Fuzzy Gamma Naive Bayes (R6 class)

In FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

Double Weighted Fuzzy Gamma Naive Bayes (R6 class)

Description

R6 implementation of the Double Weighted Fuzzy Gamma Naive Bayes classifier. Create the model with DWFuzzyGammaNaiveBayesModel$new(), train it with ⁠$fit(train, cl)⁠ and classify new observations with ⁠$predict(newdata)⁠. The functional interface DWFuzzyGammaNaiveBayes() trains and returns an object of this class.

Super class

FuzzyClassifier -> DWFuzzyGammaNaiveBayes

Methods

Public methods

• DWFuzzyGammaNaiveBayes$new()

• DWFuzzyGammaNaiveBayes$clone()

Inherited methods

• FuzzyClassifier$fit()
• FuzzyClassifier$is_fitted()
• FuzzyClassifier$predict()
• FuzzyClassifier$print()
• FuzzyClassifier$set_params()

---

DWFuzzyGammaNaiveBayes$new()

Create a new (untrained) classifier.

Usage

DWFuzzyGammaNaiveBayes$new(fuzzy = TRUE, wdelta, weta)

Arguments

fuzzy

See DWFuzzyGammaNaiveBayes().

wdelta

See DWFuzzyGammaNaiveBayes().

weta

See DWFuzzyGammaNaiveBayes().

---

DWFuzzyGammaNaiveBayes$clone()

The objects of this class are cloneable with this method.

Usage

DWFuzzyGammaNaiveBayes$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

model <- DWFuzzyGammaNaiveBayesModel$new(wdelta = rep(1/3, 3), weta = c(0.3, 0.2, 0.5))
data(GamWeightData)
model$fit(train = GamWeightData[, -4], cl = GamWeightData[, 4])
head(model$predict(GamWeightData[, -4]))
model

FuzzyClass documentation built on Oct. 22, 2026, 1:07 a.m.