Class: SimpleNaiveBayes::NaiveBayes

Inherits:
Object
  • Object
show all
Defined in:
lib/simple_naive_bayes.rb

Instance Method Summary collapse

Constructor Details

#initialize ⇒ NaiveBayes

P(cat|doc) = P(doc|cat) * P(cat) / P(doc)

P(doc) is stable, so don't care.

P(cat) = @categories_count[cat] / @all_category_num

P(doc|cat) = P(word1|cat) * P(word2|cat)....
P(word1|cat) = T(cat, word1) / (T(cat, word1) + T(cat, word2) + ...)
T(cat, word1) = @categories_word[cat][word]
(T(cat, word1) + T(cat, word2) + ...) = sum(T(cat, word))  = @categories_all_word_count[cat]

Additive smoothing

P(word1|cat) = (T(cat, word1) + a)  / sum(T(cat, word) + a))
sum(T(cat, word) + a) =  sum(T(cat, word)) + @all_word_set.length() * @additive = @laplace_categories_all_word_count[cat] 

arg max P(cat|doc)  =  arg max log(P(cat|doc))
log(P(cat|doc)) = log(P(doc|cat)) + log( P(cat))

log(P(cat)) =  log(@categories_count[cat]) - log(@all_category_num)

log(P(doc|cat)) = log(P(word1|cat)) + log(P(word2|cat)) + ....
log(P(word1|cat)) = log(T(cat, word1)) - log(sum(T(cat, word)))

http://aidiary.hatenablog.com/entry/20100613/1276389337



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# File 'lib/simple_naive_bayes.rb', line 37

def initialize()
  @all_category_num = 0
  @all_word_set = Set.new
  @categories_count = Hash.new(0)

  @categories_word = Hash.new
  @categories_all_word_count = Hash.new(0)
  @laplace_categories_all_word_count = Hash.new(0)
  @additive = 0.5
end

Instance Method Details

#calc_category_probability(category) ⇒ Object 



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# File 'lib/simple_naive_bayes.rb', line 99

def calc_category_probability(category)
  Math.log2(@categories_count[category]) - Math.log2(@all_category_num)
end

#calc_document_category(doc, category) ⇒ Object

log(P(doc|cat)) = log(P(word1|cat)) + log(P(word2|cat)) + .…



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# File 'lib/simple_naive_bayes.rb', line 104

def calc_document_category(doc, category)
  probability = 0

  # log(P(word1|cat)) + log(P(word2|cat)) + ....
  doc.each do |word|
    # log(T(cat, word1)) 
    # Additive smoothing
    category_word = Math.log2(@categories_word[category][word] + @additive) 

    # sum(T(cat, word) + 1))
    all_category_word = Math.log2(@laplace_categories_all_word_count[category])

    # log(P(word1|cat)) = log(T(cat, word1) + 1) - log(sum(T(cat, word) + 1))
    prob = category_word - all_category_word
    probability += prob if prob.finite?
  end
  probability
end

#classify(doc) ⇒ Object

classify and return best category



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# File 'lib/simple_naive_bayes.rb', line 68

def classify(doc)
  result = classify_with_all_result(doc)

  return nil unless result

  best = result.max_by { |classify_relust| classify_relust[1] }
  best[0]
end

#classify_with_all_result(doc) ⇒ Object

classify and return all category’s probability get all log(P(cat|doc)) return [ [category1, probability1], [category2, probability2]… ]



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# File 'lib/simple_naive_bayes.rb', line 80

def classify_with_all_result(doc)
  result = []
  return nil unless doc

  @categories_count.keys().each do |category|
    # log(P(doc|cat))
    document_category = calc_document_category(doc, category)

    # log(P(cat)) =  log(@categories_count[cat]) - log( @all_category_num )
    category_probability = calc_category_probability(category)

    # log(P(cat|doc)) = log(P(doc|cat)) + log(P(cat))
    category_document_probability = document_category + category_probability

    result << [category, category_document_probability]
  end
  result
end

#training(category, doc) ⇒ Object 



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# File 'lib/simple_naive_bayes.rb', line 51

def training(category, doc)
  @categories_count[category] += 1
  @all_category_num += 1

  @categories_word[category] = Hash.new(0) unless @categories_word.key?(category) 
  doc.each do |word|
    @all_word_set.add(word)
    @categories_word[category][word] += 1
    @categories_all_word_count[category] += 1
  end

  # sum(T(cat, word) + 1))
  # Additive smoothing
  @laplace_categories_all_word_count[category] = @categories_all_word_count[category] + @all_word_set.length() * @additive
end