def main(neutral):
get_documents(15, neutral)
"""for element in training_list:
print element.vector
print element.opinion"""
result = training_nb(true_list, neutral)
print apply_nb(result, "I do not really like this film", neutral)
def main(neutral):
get_documents(15, neutral)
"""for element in training_list:
print element.vector
print element.opinion"""
result = training_nb(true_list, neutral)
print apply_nb(result, "I do not really like this film", neutral)
def store_training(neutral):
if neutral:
database_name = "database3"
else:
database_name = "database2"
get_documents(15, neutral)
training_result = training_nb(true_list, neutral)
with open(database_name, 'wb') as file:
my_pickler = pickle.Pickler(file)
my_pickler.dump(training_result)
def store_training(neutral):
if neutral:
database_name = "database3"
else:
database_name = "database2"
get_documents(15, neutral)
training_result = training_nb(true_list, neutral)
with open(database_name, 'wb') as file:
my_pickler = pickle.Pickler(file)
my_pickler.dump(training_result)
def main(neutral):
get_documents(15, neutral)
"""for element in training_list:
print element.vector
print element.opinion"""
result = training_nb(true_list, neutral)
print apply_nb(result, "I do not really like this film", neutral)
neutral = False
# main(neutral)
get_documents(15, neutral)
#print cross_validation(25, 98)
print cross_validation(2, 98, neutral)
result = 0
maximum = 0
count = 0
i_max = 0
j_max = 0
for j in range(1, 10):
for i in range(60, 98):
result = cross_validation(j, i, neutral)
if result > maximum:
maximum = result
def main(neutral):
get_documents(15, neutral)
"""for element in training_list:
print element.vector
print element.opinion"""
result = training_nb(true_list, neutral)
print apply_nb(result, "I do not really like this film", neutral)
neutral = False
# main(neutral)
get_documents(15, neutral)
#print cross_validation(25, 98)
print cross_validation(2, 98, neutral)
result = 0
maximum = 0
count = 0
i_max = 0
j_max = 0
for j in range(1, 10):
for i in range(60,98):
result = cross_validation(j, i, neutral)
if result > maximum:
