WSEAS Transactions on Communications
Print ISSN: 1109-2742, E-ISSN: 2224-2864
Volume 23, 2024
Techniques for Data Augmentation and Their Impact on Long-Range Dependence and Applications
Authors: , ,
Abstract: Data augmentation is a common approach to enhance datasets for training machine learning models. This study employs five distinct techniques to generate augmented datasets. Furthermore, eight measures are applied to assess datasets both before and after augmentation techniques. A critical requirement is that any augmentation should preserve the fundamental properties of the original dataset. The study reveals that certain augmentation methods can disrupt the long-range dependence on Internet traffic data (ITD) with distributed denial of service (DDoS) attacks (DDoS ITD). These DDoS ITDs originate from stochastic and bursty environments, affecting the probability mass function (PMF) and data labeling.
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Keywords: Long-range dependence, data augmentation, Internet traffic data, speech sound data, probability mass function, dataset evaluation measures
Pages: 60-75
DOI: 10.37394/23204.2024.23.9