@inproceedings{87c3bb867f2f4da38ceb8775501d0df9,
title = "Performance evaluation of sampling-based large-scale clustering algorithms",
abstract = "Using benchmark datasets, we study the performances of three efficient clustering algorithms which find cluster centers using a fixed number of random samples. The algorithms are also compared with two other (well-known) algorithms, namely k-means and PAM. One of the efficient algorithms, CLARA, is well-known while the other two, k-means-lite and PAM-lite, were introduced recently. CLARA and PAM-lite are based on the k-medoids approach, while k-means-lite adopts the k-means approach. The study shows that k-means-lite is the most efficient, followed by PAM-lite which is faster than CLARA. PAM-lite exhibits the best balance of efficiency and accuracy; it produces the most competitive results relative to PAM which is the most accurate but most inefficient.",
keywords = "CLARA, PAM, PAM-lite, accurate, efficient, k-means, k-means-lite, k-medoids, large datasets",
author = "Olukanmi, {Peter O.} and Fulufhelo Nelwamondo and Tshilidzi Marwala",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019 ; Conference date: 28-01-2019 Through 30-01-2019",
year = "2019",
month = may,
day = "1",
doi = "10.1109/RoboMech.2019.8704854",
language = "English",
series = "Proceedings - 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "194--199",
booktitle = "Proceedings - 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2019",
address = "United States",
}