def simpleRunDT(self, train_ratio = 0.75, function = 1):
# split train data and test data
train_data, test_data, train_data_label, test_data_label = self.randomSplit(train_ratio, self.data, self.data_label)
# train
dt = tree.DT()
if function == 0:
dt.train(data = train_data, data_label = train_data_label, fun = dt.infoGain)
else:
dt.train(data = train_data, data_label = train_data_label, fun = dt.giniIndex)
# test
predictions = dt.test(test_data)
accuracy = sum([1 for label, pred in zip(test_data_label, predictions) if label == pred]) / len(predictions)
print("accuracy is: %f" %(accuracy))
return accuracy
