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Sinopsis
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 libro.
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.
?"Sobre este título" puede pertenecer a otra edición de este libro.
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Anomaly Detection Principles and Algorithms
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Anomaly Detection Principles and Algorithms
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Anomaly Detection Principles and Algorithms
Publicado por
Springer International Publishing AG, CH, 2019
ISBN 10: 331988445X
ISBN 13: 9783319884455
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Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Paperback. Condición: New. 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 their own 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. Softcover reprint of the original 1st ed. 2017. Nº de ref. del artículo: LU-9783319884455
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Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)
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Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)
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Anomaly Detection Principles and Algorithms (Terrorism, Security, and Computation)
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Anomaly Detection Principles and Algorithms
Publicado por
Springer International Publishing Jun 2019, 2019
ISBN 10: 331988445X
ISBN 13: 9783319884455
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 numberof algorithms are succinctly described, along with a presentation of theirstrengths and weaknesses.The authors also cover algorithms that addressdifferent kinds of problems of interest with single and multiple time seriesdata and multi-dimensional data. New ensemble anomaly detectionalgorithms are described, utilizing the benefits provided by diversealgorithms, each of which work well on some kinds of data.With advancements in technology and the extensive use of the internet asa medium for communications and commerce, there has been atremendous increase in the threats faced by individuals and organizationsfrom attackers and criminal entities. Variations in the observable behaviorsof individuals (from others and from their own past behaviors) have beenfound to be useful in predicting potential problems of various kinds. Hencecomputer 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. 240 pp. Englisch. Nº de ref. del artículo: 9783319884455
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Imagen del vendedor
Anomaly Detection Principles and Algorithms
Publicado por
Springer International Publishing AG, CH, 2019
ISBN 10: 331988445X
ISBN 13: 9783319884455
Nuevo
Paperback
Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. 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 their own 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. Softcover reprint of the original 1st ed. 2017. Nº de ref. del artículo: LU-9783319884455
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