def soft_rmse_for(self, ground_model):
rmse = 0.0
amount_terms = 0.0
for t in Transaction.all_for(self):
rmse += ((self.probability_of(t) -
ground_model.probability_of(t))**2)
amount_terms += 1
return sqrt(rmse / float(amount_terms))
def infinite_in_sample_log_likelihood(self, ground_model):
result = 0
for t in Transaction.all_for(self):
result += (ground_model.probability_of(t) *
self.log_probability_of(t))
return result