Skip to content

Instantly share code, notes, and snippets.

@MollsReis
Created January 21, 2016 22:54
Show Gist options
  • Save MollsReis/5d58a9de3b06eaf93a4f to your computer and use it in GitHub Desktop.
Save MollsReis/5d58a9de3b06eaf93a4f to your computer and use it in GitHub Desktop.
Multinomial Naive Bayes for a bag of words
class MNB
def initialize(examples)
@examples = examples.map { |ex| [ex.first.gsub(/[^a-zA-Z]/, ' ').downcase.split, ex.last] }
@buckets = @examples.map { |ex| ex.last }.uniq
@vocab_size = @examples.map { |ex| ex.first }.flatten.uniq.count
@prob_bucket = Hash.new do |hash, bucket|
hash[bucket] = @examples.count { |ex| ex.last == bucket } / @examples.count.to_f
end
@prob_word_given_bucket = Hash.new do |hash, word_bucket|
word, bucket = word_bucket.split('__')
num = @examples.reduce(0) { |count, ex| ex.last == bucket ? count + ex.first.count(word) : count } + 1
dom = @examples.reduce(0) { |count, ex| ex.last == bucket ? count + ex.first.count : count } + @vocab_size
hash[word_bucket] = num / dom.to_f
end
end
def prob_bucket(bucket)
@prob_bucket[bucket]
end
def prob_word_given_bucket(word, bucket)
@prob_word_given_bucket[word + '__' + bucket]
end
def classify(words)
@buckets.reduce({}) do |result, bucket|
word_prob = words.split.reduce(1) { |product, word| product * prob_word_given_bucket(word, bucket) }
result[bucket] = prob_bucket(bucket) * word_prob
result
end.max_by { |k,v| v }.first
end
end
require 'csv'
puts MNB.new(CSV.new(DATA).to_a).classify('china china china tokyo japan').inspect # => "c"
__END__
china beijing china,c
china china shanghai,c
china macao,c
tokyo japan china,j
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment