print('mean of accuracy:')
print('naive bayes', np.array(results_nbc).mean())
print('decision tree', np.array(results_dtc).mean())
# 2. use test_deals.txt for classification
nbc = NaiveBayesClassifier(dataset)
dtc = DecisionTreeClassifier(dataset)
print('naive bayes classification:')
for text in test_dat:
print(text, nbc.classify(text))
print('decision tree classification:')
for text in test_dat:
print(text, dtc.classify(text))
# other classifiers ...
#########################################enf of task3.py
###########################################task3b.py
""" Classification
The objective of this task is to build a classifier that can tell us whether a new, unseen deal
requires a coupon code or not.
We would like to see a couple of steps:
