Class: SimpleClassifier::Bayes

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

Instance Method Summary collapse

Constructor Details

#initialize(*categories) ⇒ 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 'Interesting', 'Uninteresting', 'Spam'


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# File 'lib/simple_classifier/bayes.rb', line 11

def initialize(*categories)
  @categories = Hash.new
  categories.each { |category| @categories[category.prepare_category_name] = Hash.new }
  @total_words = 0
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"


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# File 'lib/simple_classifier/bayes.rb', line 92

def method_missing(name, *args)
  category = name.to_s.gsub(/(un)?train_([\w]+)/, '\2').prepare_category_name
  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.



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# File 'lib/simple_classifier/bayes.rb', line 121

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

#categoriesObject

Provides a list of category names For example:

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


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# File 'lib/simple_classifier/bayes.rb', line 108

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



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# File 'lib/simple_classifier/bayes.rb', line 62

def classifications(text)
  score = Hash.new
  @categories.each do |category, category_words|
    score[category.to_s] = 0
    category_words_total = sum_of_values(category_words)
    text.word_hash.each do |word, count|
      word_weight = category_words.has_key?(word) ? category_words[word] : 0.1
      score[category.to_s] += Math.log(word_weight/category_words_total.to_f)
    end
  end
  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'


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# File 'lib/simple_classifier/bayes.rb', line 80

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


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# File 'lib/simple_classifier/bayes.rb', line 24

def train(category, text)
  category = category.prepare_category_name
  text.word_hash.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"


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# File 'lib/simple_classifier/bayes.rb', line 41

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