Class: Classifier::Bayes

Inherits:
Base
  • Object
show all
Defined in:
lib/classifier/bayes.rb

Instance Method Summary collapse

Methods inherited from Base

#clean_word_hash, #prepare_category_name, #remove_stemmer, #without_punctuation, #word_hash

Constructor Details

#initialize(options = {}) ⇒ Bayes

The class can be created with one or more categories, each of which will be initialized and given a training method. E.g., 

    b = Classifier::Bayes.new :categories => ['Interesting', 'Uninteresting', 'Spam']
you can specify language and encoding parameters for stemmer

(default values - :language => ‘en’, :encoding => ‘UTF_8’)

b = Classifier::Bayes.new :categories => ['Interesting', 'Uninteresting', 'Spam'], :language => 'ru'



17
18
19
20
21
22
23
 
# File 'lib/classifier/bayes.rb', line 17

def initialize(options = {})
  @categories = Hash.new
  options.reverse_merge!(:categories => [])
  options[:categories].each { |category| @categories[prepare_category_name(category)] = Hash.new }
  @total_words = 0
  super
end

Dynamic Method Handling

This class handles dynamic methods through the method_missing method

#method_missing(name, *args) ⇒ Object

Provides training and untraining methods for the categories specified in Bayes#new For example:

b = Classifier::Bayes.new 'This', 'That', 'the_other'
b.train_this "This text"
b.train_that "That text"
b.untrain_that "That text"
b.train_the_other "The other text"



100
101
102
103
104
105
106
107
108
109
 
# File 'lib/classifier/bayes.rb', line 100

def method_missing(name, *args)
  category = prepare_category_name(name.to_s.gsub(/(un)?train_([\w]+)/, '\2'))
  if @categories.has_key? category
    args.each { |text| eval("#{$1}train(category, text)") }
  elsif name.to_s =~ /(un)?train_([\w]+)/
    raise StandardError, "No such category: #{category}"
  else
    super  #raise StandardError, "No such method: #{name}"
  end
end

Instance Method Details

#add_category(category) ⇒ Object Also known as: append_category

Allows you to add categories to the classifier. For example:

b.add_category "Not spam"

WARNING: Adding categories to a trained classifier will result in an undertrained category that will tend to match more criteria than the trained selective categories. In short, try to initialize your categories at initialization.



129
130
131
 
# File 'lib/classifier/bayes.rb', line 129

def add_category(category)
  @categories[prepare_category_name(category)] = Hash.new
end

#categories ⇒ Object

Provides a list of category names For example:

b.categories
=>   ['This', 'That', 'the_other']



116
117
118
 
# File 'lib/classifier/bayes.rb', line 116

def categories # :nodoc:
  @categories.keys.collect {|c| c.to_s}
end

#classifications(text) ⇒ Object

Returns the scores in each category the provided text. E.g.,

b.classifications "I hate bad words and you"
=>  {"Uninteresting"=>-12.6997928013932, "Interesting"=>-18.4206807439524}

The largest of these scores (the one closest to 0) is the one picked out by #classify



70
71
72
73
74
75
76
77
78
79
80
81
 
# File 'lib/classifier/bayes.rb', line 70

def classifications(text)
  score = Hash.new
  @categories.each do |category, category_words|
    score[category.to_s] = 0
    total = category_words.values.sum
    word_hash(text).each do |word, count|
      s = category_words.has_key?(word) ? category_words[word] : 0.1
      score[category.to_s] += Math.log(s/total.to_f)
    end
  end
  return score
end

#classify(text) ⇒ Object

Returns the classification of the provided text, which is one of the categories given in the initializer. E.g.,

b.classify "I hate bad words and you"
=>  'Uninteresting'



88
89
90
 
# File 'lib/classifier/bayes.rb', line 88

def classify(text)
  (classifications(text).sort_by { |a| -a[1] })[0][0]
end

#marshal_dump ⇒ Object 



135
136
137
 
# File 'lib/classifier/bayes.rb', line 135

def marshal_dump
  [@categories, @total_words, @options ]
end

#marshal_load(data) ⇒ Object 



139
140
141
 
# File 'lib/classifier/bayes.rb', line 139

def marshal_load(data)
  @categories, @total_words, @options = data
end

#train(category, text) ⇒ Object

Provides a general training method for all categories specified in Bayes#new For example:

b = Classifier::Bayes.new 'This', 'That', 'the_other'
b.train :this, "This text"
b.train "that", "That text"
b.train "The other", "The other text"



32
33
34
35
36
37
38
39
 
# File 'lib/classifier/bayes.rb', line 32

def train(category, text)
  category = prepare_category_name(category)
  word_hash(text).each do |word, count|
    @categories[category][word]     ||=     0
    @categories[category][word]      +=     count
    @total_words += count
  end
end

#untrain(category, text) ⇒ Object

Provides a untraining method for all categories specified in Bayes#new Be very careful with this method.

For example:

b = Classifier::Bayes.new 'This', 'That', 'the_other'
b.train :this, "This text"
b.untrain :this, "This text"



49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
 
# File 'lib/classifier/bayes.rb', line 49

def untrain(category, text)
  category = prepare_category_name(category)
   word_hash(text).each do |word, count|
    if @total_words >= 0
      orig = @categories[category][word] || 0
      @categories[category][word]     ||=     0
      @categories[category][word]      -=     count
      if @categories[category][word] <= 0
        @categories[category].delete(word)
        count = orig
      end
      @total_words -= count
    end
  end
end