FuzzyGeoNaiveBayes: Fuzzy Naive Bayes Geometric Classifier

In FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

Fuzzy Naive Bayes Geometric Classifier

Description

FuzzyGeoNaiveBayes Naive Bayes Geometric Classifier

Usage

FuzzyGeoNaiveBayes(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	how many cores of the computer do you want to use (default = 2)
fuzzy	boolean variable to use the membership function

Value

A vector of classifications

References

\insertRef

ferreira2023FuzzyClass

Examples

set.seed(1) # determining a seed
class1 <- data.frame(vari1 = rgeom(100,prob = 0.2),
                     vari2 = rgeom(100,prob = 0.2),
                     vari3 = rgeom(100,prob = 0.2), class = 1)
class2 <- data.frame(vari1 = rgeom(100,prob = 0.5),
                     vari2 = rgeom(100,prob = 0.5),
                     vari3 = rgeom(100,prob = 0.5), class = 2)
class3 <- data.frame(vari1 = rgeom(100,prob = 0.9),
                     vari2 = rgeom(100,prob = 0.9),
                     vari3 = rgeom(100,prob = 0.9), class = 3)
data <- rbind(class1,class2,class3)

# Splitting into Training and Testing
split <- caTools::sample.split(t(data[, 1]), SplitRatio = 0.7)
Train <- subset(data, split == "TRUE")
Test <- subset(data, 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[, -4]
fit_NBT <- FuzzyGeoNaiveBayes(
  train = Train[, -4],
  cl = Train[, 4], cores = 2
)

pred_NBT <- predict(fit_NBT, test)

head(pred_NBT)
head(Test[, 4])

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