lib/ankusa/naive_bayes.rb in ankusa-0.0.8 vs lib/ankusa/naive_bayes.rb in ankusa-0.0.9

@@ -1,6 +1,7 @@
 module Ankusa
+  INFTY = 1.0 / 0.0
 
   class NaiveBayesClassifier
     include Classifier
 
     def classify(text, classes=nil)
@@ -10,11 +11,11 @@
     
     # 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] 
+        result[k] = (result[k] == INFTY) ? 0 : 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 }
@@ -26,19 +27,22 @@
       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) }
+        classnames.each { |k| 
+          # log likelihood should be infinity if we've never seen the klass
+          result[k] += probs[k] > 0 ? (Math.log(probs[k]) * count) : INFTY
+        }
       }
 
-      # add the prior and exponentiate
+      # add the prior
       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