FuzzyExponentialNaiveBayes: Fuzzy Exponential Naive Bayes

In FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

Fuzzy Exponential Naive Bayes

Description

FuzzyExponentialNaiveBayes Fuzzy Exponential Naive Bayes

Usage

FuzzyExponentialNaiveBayes(train, cl, cores = 2, fuzzy = TRUE)

Arguments

train	matrix or data frame of training set cases.
cl	factor of true classifications of training set
cores	how many cores of the computer do you want to use to use for prediction (default = 2)
fuzzy	boolean variable to use the membership function

Value

A vector of classifications

References

\insertRef

moraes2016fuzzyFuzzyClass

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 <- FuzzyExponentialNaiveBayes(
  train = Train[, -5],
  cl = Train[, 5], cores = 2
)

pred_NBT <- predict(fit_NBT, test)

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

FuzzyClass documentation built on May 29, 2024, 8:37 a.m.