Non-Negative Latent Factor Dimensionality-Minimizing Intra-Class  Compactness for Feature Extraction in IoV Security

Raavi Deepthi

Non-Negative Latent Factor Dimensionality-Minimizing Intra-Class Compactness for Feature Extraction in IoV Security

Authors

Raavi Deepthi

Keywords:

Feature Extraction, Non-Negative Factorization, Dimensionality Reduction, Intra Class Compactness, IoV Security

Abstract

High-dimensional feature spaces inInternet of Vehicles datasets create computational challenges and potential overfitting risks

References

Taslimasa, H.; Dadkhah, S.; Neto, E.C.P.; Xiong, P.; Ray, S.; Ghorbani, A.A. Security issues in Internet of Vehicles (IoV): A comprehensive survey. Internet Things 2023, 22, 100809. [Google Scholar] [CrossRef]

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Published

2024-12-05

How to Cite

Raavi Deepthi. (2024). Non-Negative Latent Factor Dimensionality-Minimizing Intra-Class Compactness for Feature Extraction in IoV Security . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2363–2367. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4318