# Import modules.
>>> import sklearn.model_selection
>>> import random_mac
# Make a dataset.
>>> data, labels = random_mac.dataset.make(
... 2,
... oui_file="./oui.csv",
... cid_file="./cid.csv"
... )
# Split the dataset.
>>> training_data, testing_data, training_labels, testing_labels = sklearn.model_selection.train_test_split(data, labels)
# Make, train, and test a classifier.
>>> classifier = random_mac.classifier.make()
>>> classifier = random_mac.classifier.train(
... classifier,
... training_data,
... training_labels
... )
>>> score = random_mac.classifier.test(
... classifier,
... testing_data,
... testing_labels
... )
>>> print("score = {}%".format(str(int(100 * score))))
score = 83%
# Save the classifier.
>>> random_mac.classifier.save(
... classifier,
... file="./random-mac-classifier.pickled"
... )