Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. reprint edition. 240 pages. 9.50x6.50x0.75 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing AG, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
Anbieter: Better World Books Ltd, Dunfermline, Vereinigtes Königreich
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In den WarenkorbZustand: Very Good. Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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Taschenbuch. Zustand: Neu. Anomaly Detection Principles and Algorithms | Kishan G. Mehrotra (u. a.) | Taschenbuch | 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.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 331988445X ISBN 13: 9783319884455
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.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing Jan 2018, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
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.
Sprache: Englisch
Verlag: Springer International Publishing, 2018
ISBN 10: 3319675249 ISBN 13: 9783319675244
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.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 218,25
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In den WarenkorbHardcover. Zustand: Brand New. 217 pages. 9.25x6.25x0.75 inches. In Stock.