Anomaly Detection Principles and Algorithms
Idioma: inglés
Editorial: Springer, 2019
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Anomaly Detection Principles and Algorithms | Kishan G. Mehrotra (u. a.) | Taschenbuch | Terrorism, Security, and Computation | xxii | Englisch | 2019 | Springer | EAN 9783319884455 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
N° de ref. del artículo 115141034
- Título
- Anomaly Detection Principles and Algorithms
- Autor
- Kishan G. Mehrotra (u. a.)
- Editorial
- Springer
- Año de publicación
- 2019
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 331988445X
- ISBN 13
- 9783319884455
- Peso del artículo
- 371 gramos
- Dimensiones
- 235 x 155 x 14 mm
- Serie
- Libro 5 de 7: Terrorism, Security, and Computation
- Catálogos de vendedores
- Bücher
Presents new algorithms for static and time series datasets
Introduces new ensemble methods for improved anomaly detection
Covers rank-based anomaly detection algorithms
Discusses the pros and cons of various approaches used for anomaly detection
“Sinopsis” puede pertenecer a otra edición de este título.
De la contraportada
This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large number of algorithms are succinctly described, along with a presentation of their strengths and weaknesses.
The authors also cover algorithms that address different kinds of problems of interest with single and multiple time series data and multi-dimensional data. New ensemble anomaly detection algorithms are described, utilizing the benefits provided by diverse algorithms, each of which work well on some kinds of data.
With advancements in technology and the extensive use of the internet as a medium for communications and commerce, there has been a tremendous increase in the threats faced by individuals and organizations from attackers and criminal entities. Variations in the observable behaviors of individuals (from others and from theirown past behaviors) have been found to be useful in predicting potential problems of various kinds. Hence computer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets.
This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies.
?“Acerca de” puede pertenecer a otra edición de este título.
preigu
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