Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-III 2024); Krasnoyarsk; Krasnoyarsk
Год издания: 2025
Идентификатор DOI: 10.1051/itmconf/20257204007
Аннотация: This study presents a two-level clustering method utilizing a simplified greedy procedure to enhance data processing efficiency and accuracy, particularly with large high-dimensional datasets. The two-level structure allows for the identification of broad data groups in the first stage, followed by a more granular analysis within tПоказать полностьюhese groups in the second stage, thereby accelerating the clustering process and improving result quality. The application of the k-means++ method did not yield the anticipated benefits compared to traditional random initialization. Such findings underscore the necessity for preliminary data analysis when selecting optimal clustering algorithms, as instances of complex methods failing to improve results are not uncommon. This work illustrates the importance of balance between method complexity and effectiveness in real-world applications and emphasizes the potential for increased resource expenditure without commensurate gains in clustering performance.
Журнал: ITM Web of Conferences
Номера страниц: 4007
Место издания: Krasnoyarsk