The least sample size essential for detecting changes in clustering solutions of streaming datasets.

ABSTRACT: The clustering analysis approach treats multivariate data tuples as objects and groups them into clusters based on their similarities or dissimilarities within the dataset. However, in modern world, a significant volume of data is continuously generated from diverse sources over time. In these dynamic scenarios, the data is not static but continually evolves. Consequently, the interesting patterns and inherent subgroups within the datasets also change and develop over time. The researchers have paid special attention to monitoring changes in cluster solutions of evolving streams. For this matter, several algorithms have been proposed in the literature. However, to date, no study has examined the effect of variability in cluster sizes on the evolution of cluster solutions. Moreover, no guid

SUBMITTER: Atif M 

PROVIDER: S-EPMC10878511 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature