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Contents
module Ankusa class NaiveBayesClassifier include Classifier def classify(text, classes=nil) # return the most probable class log_likelihoods(text, classes).sort_by { |c| -c[1] }.first.first end # Classes is an array of classes to look at def classifications(text, classnames=nil) result = log_likelihoods text, classnames result.keys.each { |k| result[k] = Math.exp result[k] } # normalize to get probs sum = result.values.inject { |x,y| x+y } result.keys.each { |k| result[k] = result[k] / sum } result end # Classes is an array of classes to look at def log_likelihoods(text, classnames=nil) classnames ||= @classnames result = Hash.new 0 TextHash.new(text).each { |word, count| probs = get_word_probs(word, classnames) classnames.each { |k| result[k] += (Math.log(probs[k]) * count) } } # add the prior and exponentiate doc_counts = doc_count_totals.select { |k,v| classnames.include? k }.map { |k,v| v } doc_count_total = (doc_counts.inject { |x,y| x+y } + classnames.length).to_f classnames.each { |k| result[k] += Math.log((@storage.get_doc_count(k) + 1).to_f / doc_count_total) } result end end end
Version data entries
2 entries across 2 versions & 1 rubygems
Version | Path |
---|---|
ankusa-0.0.8 | lib/ankusa/naive_bayes.rb |
ankusa-0.0.7 | lib/ankusa/naive_bayes.rb |