@inproceedings{6e4dd5be46a1429f9d576a05f554cb23,
title = "Metamorphic exploration of an unsupervised clustering program",
abstract = "Machine learning has been becoming increasingly popular and widely-used in various industry domains. The presence of the oracle problem, however, makes it difficult to ensure the quality of this kind of software. Furthermore, the popularity of machine learning and its application has attracted many users who are not experts in this field. In this paper, we report on using a recently introduced method called metamorphic exploration where we proposed a set of hypothesized metamorphic relations for an unsupervised clustering program, Weka, to enhance understanding of the system and its better use.",
keywords = "Clustering, K-means, Machine learning, Metamorphic exploration, Metamorphic testing, Unsupervised machine learning",
author = "Sen Yang and Dave Towey and Zhou, {Zhi Quan}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 4th IEEE/ACM International Workshop on Metamorphic Testing, MET 2019 ; Conference date: 26-05-2019",
year = "2019",
month = may,
doi = "10.1109/MET.2019.00015",
language = "English",
series = "Proceedings - 2019 IEEE/ACM 4th International Workshop on Metamorphic Testing, MET 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "48--54",
booktitle = "Proceedings - 2019 IEEE/ACM 4th International Workshop on Metamorphic Testing, MET 2019",
address = "United States",
}