@inproceedings{dcfce7c7727f49b1902e9c42764da451,
title = "Accuracy of clustering prediction of PAM and K-modes algorithms",
abstract = "The concept of grouping (or clustering) data points with similar characteristics is of importance when working with the data that frequently appears in everyday life. Data scientists cluster the data that is numerical in nature based on the notion of distance, usually computed using Euclidean measure. However, there are many datasets that often consists of categorical values which require alternative methods for grouping the data. That is why clustering of categorical data employs methods that rely on similarity between the values rather than distance. This work focuses on studying the ability of different clustering algorithms and several definitions of similarity to organize categorical data into groups.",
author = "Dixon, {Marc Gregory} and Stanimir Genov and Vasil Hnatyshin and Umashanger Thayasivam",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; Future of Information and Communication Conference, FICC 2018 ; Conference date: 05-04-2018 Through 06-04-2018",
year = "2019",
doi = "10.1007/978-3-030-03402-3_22",
language = "English (US)",
isbn = "9783030034016",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "330--345",
editor = "Rahul Bhatia and Kohei Arai and Supriya Kapoor",
booktitle = "Advances in Information and Communication Networks - Proceedings of the 2018 Future of Information and Communication Conference FICC, Vol. 1",
address = "Germany",
}