Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time Series

This paper presents an extensive empirical study on the integration of dimensionality reduction techniques with advanced unsupervised time series anomaly detection models, focusing on the MUTANT and Anomaly-Transformer models. The study involves a comprehensive evaluation across three different data...

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Bibliografiske detaljer

Principais autores:	Mahsun Altin, Altan Cakir
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2024-01-01
Serier:	IEEE Access
Fag:	Time series anomaly detection dimensionality reduction unsupervised learning
Online adgang:	https://ieeexplore.ieee.org/document/10559232/
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