def METHOD_NAME():
   le_classes = ['asomething', 'bsomething']
   le = preprocessing.LabelEncoder()
   le.fit(le_classes)
   filename = ['firstfile']
   host_key = np.array(['mac1'])
   tshark_srcips = np.array(["['1.1.1.1']"])
   frame_epoch = None
   instance = HostFootprint()
   assert instance.get_individual_predictions([[0.6, 0.7]], le, filename, host_key, tshark_srcips, frame_epoch) == {
        'firstfile': [{'top_role': 'bsomething', 'role_list': [('bsomething', 0.7), ('asomething', 0.6)], 'source_ip': '1.1.1.1', 'source_mac': 'mac1'}]}
   assert instance.get_individual_predictions([[0.2, 0.1]], le, filename, host_key, tshark_srcips, frame_epoch) == {
        'firstfile': [{'top_role': 'Unknown', 'role_list': [('asomething', 0.2), ('bsomething', 0.1)], 'source_ip': '1.1.1.1', 'source_mac': 'mac1'}]}