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Verlag: Springer International Publishing AG, CH, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: 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.
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Verlag: Springer International Publishing AG, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
Sprache: Englisch
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ISBN 10: 3319675249 ISBN 13: 9783319675244
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In den WarenkorbHardback. Zustand: New. 1st ed. 2017. 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.
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Verlag: Springer International Publishing AG, CH, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: 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.
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Verlag: Springer International Publishing AG, CH, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
Sprache: Englisch
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In den WarenkorbHardback. Zustand: New. 1st ed. 2017. 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.
Verlag: Springer-Verlag New York Inc, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
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Verlag: Springer International Publishing, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Anomaly Detection Principles and Algorithms | Kishan G. Mehrotra (u. a.) | Taschenbuch | xxii | Englisch | 2019 | Springer International Publishing | EAN 9783319884455 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Verlag: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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In den WarenkorbHardcover. Zustand: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Verlag: Springer International Publishing, Springer International Publishing Jan 2018, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. 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 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.
Verlag: Springer International Publishing, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
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In den WarenkorbHardcover. Zustand: Brand New. 217 pages. 9.25x6.25x0.75 inches. In Stock.
Verlag: Springer International Publishing Jun 2019, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: 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.
Verlag: Springer International Publishing, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents new algorithms for static and time series datasetsIntroduces new ensemble methods for improved anomaly detectionCovers rank-based anomaly detection algorithmsDiscusses the pros and cons of various approaches used for anomaly.
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In den WarenkorbZustand: New. Print on Demand.
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Verlag: Springer International Publishing, Springer International Publishing Jun 2019, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. 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 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.