Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.


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    Title :

    FRAMEWORK FOR THE AUTOMATED DETERMINATION OF CLASSES AND ANOMALY DETECTION METHODS FOR TIME SERIES


    Additional title:

    RAHMEN ZUR AUTOMATISIERTEN BESTIMMUNG VON KLASSEN UND ANOMALIEDETEKTIONSVERFAHREN FÜR ZEITREIHEN
    CADRE POUR LA DÉTERMINATION AUTOMATIQUE DE CLASSES ET PROCÉDÉS DE DÉTECTION D'ANOMALIE POUR SÉRIES TEMPORELLES


    Contributors:

    Publication date :

    2020-03-18


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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