Class: Classifier::Bayes
Instance Method Summary collapse
-
#add_category(category) ⇒ Object
(also: #append_category)
Allows you to add categories to the classifier.
-
#categories ⇒ Object
Provides a list of category names For example: b.categories => [‘This’, ‘That’, ‘the_other’].
-
#classifications(text) ⇒ Object
Returns the scores in each category the provided
text
. -
#classify(text) ⇒ Object
Returns the classification of the provided
text
, which is one of the categories given in the initializer. -
#initialize(*categories) ⇒ Bayes
constructor
The class can be created with one or more categories, each of which will be initialized and given a training 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”.
-
#remove_category(category) ⇒ Object
Allows you to remove categories from the classifier.
-
#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”.
-
#untrain(category, text) ⇒ Object
Provides a untraining method for all categories specified in Bayes#new Be very careful with this method.
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/classifier/bayes.rb', line 10 def initialize(*categories) @categories = {} categories.each { |category| @categories[category.prepare_category_name] = {} } @total_words = 0 @category_counts = Hash.new(0) @category_word_count = Hash.new(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/classifier/bayes.rb', line 102 def method_missing(name, *args) category = name.to_s.gsub(/(un)?train_(\w+)/, '\2').prepare_category_name if @categories.key?(category) args.each do |text| if name.to_s.start_with?('untrain_') untrain(category, text) else train(category, text) end end elsif name.to_s =~ /(un)?train_(\w+)/ raise StandardError, "No such category: #{category}" else super 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 137 def add_category(category) @categories[category.prepare_category_name] = {} 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 124 def categories # :nodoc: @categories.keys.collect(&: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 67 def classifications(text) score = {} word_hash = text.word_hash training_count = @category_counts.values.inject { |x, y| x + y }.to_f @categories.each do |category, category_words| score[category.to_s] = 0 total = (@category_word_count[category] || 1).to_f word_hash.each_key do |word| s = category_words.key?(word) ? category_words[word] : 0.1 score[category.to_s] += Math.log(s / total) end # now add prior probability for the category s = @category_counts.key?(category) ? @category_counts[category] : 0.1 score[category.to_s] += Math.log(s / training_count) 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/classifier/bayes.rb', line 90 def classify(text) (classifications(text).sort_by { |a| -a[1] })[0][0] end |
#remove_category(category) ⇒ Object
Allows you to remove categories from the classifier. For example:
b.remove_category "Spam"
WARNING: Removing categories from a trained classifier will result in the loss of all training data for that category. Make sure you really want to do this before calling this method.
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# File 'lib/classifier/bayes.rb', line 151 def remove_category(category) category = category.prepare_category_name raise StandardError, "No such category: #{category}" unless @categories.key?(category) @total_words -= @category_word_count[category].to_i @categories.delete(category) @category_counts.delete(category) @category_word_count.delete(category) 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 25 def train(category, text) category = category.prepare_category_name @category_counts[category] += 1 text.word_hash.each do |word, count| @categories[category][word] ||= 0 @categories[category][word] += count @total_words += count @category_word_count[category] += 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 44 def untrain(category, text) category = category.prepare_category_name @category_counts[category] -= 1 text.word_hash.each do |word, count| next unless @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 @category_word_count[category] -= count if @category_word_count[category] >= count @total_words -= count end end |