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())
