FuzzyTrapezoidalNaiveBayes: Fuzzy Naive Bayes Trapezoidal Classifier

In FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

Fuzzy Naive Bayes Trapezoidal Classifier

Description

FuzzyTrapezoidalNaiveBayes Fuzzy Naive Bayes Trapezoidal Classifier

Usage

FuzzyTrapezoidalNaiveBayes(train, cl, cores = 2, fuzzy = T)

Arguments

train	matrix or data frame of training set cases.
cl	factor of true classifications of training set
cores	kept for backward compatibility; prediction is vectorized and does not start parallel workers (default = 2)
fuzzy	boolean variable to use the membership function

Value

A vector of classifications

References

\insertRef

de2022fuzzyFuzzyClass

Examples

set.seed(1) # determining a seed
data(iris)

# Splitting into Training and Testing
split <- caTools::sample.split(t(iris[, 1]), SplitRatio = 0.7)
Train <- subset(iris, split == "TRUE")
Test <- subset(iris, split == "FALSE")
# ----------------
# matrix or data frame of test set cases.
# A vector will be interpreted as a row vector for a single case.
test <- Test[, -5]
fit_NBT <- FuzzyTrapezoidalNaiveBayes(
  train = Train[, -5],
  cl = Train[, 5], cores = 2
)

pred_NBT <- predict(fit_NBT, test)

head(pred_NBT)
head(Test[, 5])

FuzzyClass documentation built on Oct. 9, 2026, 5:07 p.m.