FuzzyClass (version 0.1.7)

FuzzyTriangularNaiveBayes: Fuzzy Naive Bayes Triangular Classifier

Description

FuzzyTriangularNaiveBayes Fuzzy Naive Bayes Triangular Classifier

Usage

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

Value

A vector of classifications

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

References

de2020onlineFuzzyClass

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

pred_NBT <- predict(fit_NBT, test)

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