R implementation of the Naive Bayes classifier example from [Wikipedia](http://en.wikipedia.org/wiki/Naive_Bayes_classifier#Examples).

naivebayes.r

# naivebayes.txt
#
# sex height weight  footsize
# male  6    180	12
# male	5.92 190	11
# male	5.58	170	12
# male	5.92	165	10
# female 5	100	6
# female 5.5	150	8
# female 5.42	130	7
# female 5.75	150	9

library("data.table")

train <- function (dt) {
  return(dt[,list(meanHeight=mean(height), varHeight=sd(height),
                  meanWeight=mean(weight), varWeight=sd(weight),
                  meanFootsize=mean(footsize), varFootsize=sd(footsize)), by=sex])
}

classify <- function (classifier, sample) {
  posterior <- function (sample, class_prior, class) {
    p_height <- dnorm(sample$height, class$meanHeight, class$varHeight)
    p_weight <- dnorm(sample$weight, class$meanWeight, class$varWeight)
    p_footsize <- dnorm(sample$footsize, class$meanFootsize, class$varFootsize)
    return(class_prior * p_height * p_weight * p_footsize)
  }
  
  class_male <- classifier[which(classifier$sex == 'male'),]
  class_female <- classifier[which(classifier$sex == 'female'),]
  
  prior_male <- 0.5
  prior_female <- 0.5
  
  return(list(male=posterior(sample, prior_male, class_male),
              female=posterior(sample, prior_female, class_female)))
}

training_set <- data.table(read.table('naivebayes.txt', header=TRUE))
sample = data.table(height=6, weight=130, footsize=8)

classifier <- train(training_set)
result = classify(classifier, sample)

cat('posterior(male) =', result$male)
cat('posterior(female) =', result$female)