def compute_info_gain(word_list, language_model):
word_dict = dict()
for word in word_list:
if word in word_dict:
word_dict[word] +=1
else:
word_dict[word] = 1
wlm = LanguageModel(term_dict = word_dict)
ig = 0.0
for word in word_dict:
pw = wlm.get_term_prob(word)
pwc = language_model.get_term_prob(word)
g = 0.0
if pwc > 0.0:
g = pw * (math.log(pwc)- math.log(pw))
ig += g
return ig
