from adaboost import AdaBoost
from naivebayes import NaiveBayes
xfilename = sys.argv[1]
yfilename = sys.argv[2]
testset = sys.argv[3]
print("training naive bayes...")
nb = NaiveBayes()
ab = AdaBoost()
dataset = convert(xfilename, yfilename)
validation_set_size = 10000
train_set, validation_set = split_train_validation(dataset,
validation_set_size)
num_to_train_on = 10000000
time_before("training adaboost")
ab.train_set(dataset[:num_to_train_on])
time_after("training adaboost")
time_before("training naive bayes")
nb.train_set(dataset[:num_to_train_on])
time_after("training naive bayes")
kg_validations_nb = []
kg_validations_ab = []
for i in validation_set:
kg_validations_nb.append(nb.predict(*i[1:]) == i[0])
kg_validations_ab.append(ab.predict(*i[1:]) == i[0])
# print("Errors nb: %s " % sum([0 if i else 1 for i in kg_validations_nb]))
print("Errors ab: %s " % sum([0 if i else 1 for i in kg_validations_ab]))
