GeMSyD: Generic Framework for Synthetic Data Generation

In the era of data-driven technologies, the need for diverse and high-quality datasets for training and testing machine learning models has become increasingly critical. In this article, we present a versatile methodology, the Generic Methodology for Constructing Synthetic Data Generation (GeMSyD),...

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Bibliographic Details
Main Authors: Ramona Tolas, Raluca Portase, Rodica Potolea
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Data
Subjects:
Online Access:https://www.mdpi.com/2306-5729/9/1/14