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'



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# 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"



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# 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.



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# 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']



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# 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



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# 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'



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

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

#marshal_dump ⇒ Object 



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

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

#marshal_load(data) ⇒ Object 



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# 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"



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# 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"



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# 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