16 124 897 livres à l’intérieur 175 langues
2 047 051 livres numériques à l’intérieur 101 langues
Cela ne vous convient pas ? Aucun souci à se faire ! Vous pouvez renvoyer le produit dans les 30 jours
Impossible de faire fausse route avec un bon d’achat. Le destinataire du cadeau peut choisir ce qu'il veut parmi notre sélection.
Politique de retour sous 30 jours
An outlier or anomaly is a data point that is inconsistent with the rest of the data population. Outlier or anomaly detection has been used for centuries to detect and remove anomalous observations from data. It is used to monitor vital infrastructure such as utility distribution networks, transportation networks, machinery or computer networks for faults. Detection can identify faults before they escalate with potentially catastrophic consequences. Today, principled and systematic detection techniques are used, drawn from the full gamut of Computer Science and Statistics. The book forms a survey of techniques covering statistical, proximity-based, density-based, neural, natural computation, machine learning, distributed and hybrid systems. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review. It aims to provide the reader with a feel of the diversity and multiplicity of techniques available. The survey should be useful to advanced undergraduate and postgraduate computer and library/information science students and researchers analysing and developing outlier and anomaly detection systems.