def show_results(self,gold,test): from nltk import ConfusionMatrix correct = 0 for index,result in enumerate(gold): if result == test[index]: correct +=1 print 'Accuracy: {:.2%}'.format(float(correct) / float(len(gold))) cm = ConfusionMatrix(gold, test) print cm.pp()
def confusion_matrix(gold,guess): correct = 0 total = len(gold) for i in range(len(gold)): if guess[i] == gold[i]: correct += 1 accuracy = float(correct) / float(total) print('Accuracy: {:.2%}'.format(accuracy)) # Confusion Matrix cm = ConfusionMatrix(gold, guess) print (cm.pp())
def confusion_matrix(gold, guess): correct = 0 total = len(gold) for i in range(len(gold)): if guess[i] == gold[i]: correct += 1 accuracy = float(correct) / float(total) print('Accuracy: {:.2%}'.format(accuracy)) # Confusion Matrix cm = ConfusionMatrix(gold, guess) print(cm.pp())