FuzzyHipergeometricNaiveBayes: Fuzzy Hipergeometric Naive Bayes

In FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

Fuzzy Hipergeometric Naive Bayes

Description

FuzzyHipergeometricNaiveBayes Fuzzy Hipergeometric Naive Bayes

Usage

FuzzyHipergeometricNaiveBayes(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	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

ferreira2025newFuzzyClass

Examples

set.seed(1) # determining a seed

substituir_zero <- function(x) {
  if (x == 0) {
    while(1){
     new_valor <- rhyper(1,3,30,10)
      if(new_valor != 0){
        return(new_valor)
      }
    }
  } else {
    return(x)
  }
}

#Building dataframe
class1 <- data.frame(rhyper(72,3,30,10), 
                     sample(seq(1,5),72,replace = TRUE), class = "Bem treinado")
colnames(class1)[1] <- "sucessos"
class1$sucessos <- sapply(class1$sucessos, substituir_zero)
colnames(class1)[2] <- "tentativas"
colnames(class1)[3] <- "avaliação"
class2 <- data.frame(rhyper(72,3,17,12), 
                     sample(seq(4,7),72,replace = TRUE), class = "Mediano")
colnames(class2)[1] <- "sucessos"
colnames(class2)[2] <- "tentativas"
colnames(class2)[3] <- "avaliação"
class3 <- data.frame(rhyper(72,3,9,11),
                     sample(seq(7,10),72,replace = TRUE), class = "Precisa treinar")
colnames(class3)[1] <- "sucessos"
colnames(class3)[2] <- "tentativas"
colnames(class3)[3] <- "avaliação"
data <- rbind(class1,class2,class3)


#spliting dataframe
split <- caTools::sample.split(t(data[, 1]), SplitRatio = 0.7)
Train <- subset(data, split == "TRUE")
Test <- subset(data, split == "FALSE")

test <- Test[, -3]
fit_NHT <- FuzzyHipergeometricNaiveBayes(
 train = Train[, -3],
 cl = Train[, 3], cores = 2
)

pred_NHT <- predict(fit_NHT, test)

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