125911 20250113143110.0 doi 10.1016/j.softx.2023.101363 sideral 133435 ART-2023-133435 eng Bernardi, S. Universidad de Zaragoza (orcid)0000-0002-2605-6243 Tegdet: an extensible Python library for anomaly detection using time evolving graphs 2023 Access copy available to the general public Unrestricted This paper presents tegdet, a new Python library for anomaly detection in unsupervised approaches. The input of the library is a univariate time series, representing observations of a given phenomenon. Then, tegdet identifies anomalous epochs, i.e., time intervals where the observations differ in a given percentile of a baseline distribution. Epochs are represented by time evolving graphs and the baseline distribution is given by the dissimilarities between a reference graph and the graphs of the epochs. Currently, the library implements 28 dissimilarity metrics, i.e., 28 different anomaly detection techniques, and its extensible design allows to easily introduce new ones. tegdet exposes a complete functionality to carry out the anomaly detection, through a straightforward designed API. Summarizing, to the best of our knowledge, tegdet is the first publicly available library, based on time evolving graphs, for anomaly detection in time series. Our experimentation shows promising results. For example, Clark and Divergence techniques can achieve an accuracy of 100%, while the time to build the model and predict lasts for few hundreds milliseconds. info:eu-repo/grantAgreement/ES/MICINN/PID2020-113969RB-I00 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 2.4 2023 COMPUTER SCIENCE, SOFTWARE ENGINEERING 54 / 132 = 0.409 2023 Q2 T2 0.544 2023 Computer Science Applications 2023 Q2 Software 2023 Q3 5.5 2023 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Javierre, R. Merseguer, J. Universidad de Zaragoza (orcid)0000-0002-8917-6584 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 22 (2023), 101363 [7 pp.] SoftwareX 2352-7110 Datos asociados-DiasporeUnizar https://github.com/DiasporeUnizar/TEG 1437274 http://zaguan.unizar.es/record/125911/files/texto_completo.pdf Versión publicada 2425263 http://zaguan.unizar.es/record/125911/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:125911 articulos driver 2025-01-13-14:30:25 ARTICLE