How ANOMALY DETECTION works in time series using the Holt-Winters Algorithm

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  • Опубликовано: 2 июн 2024
  • This video explains how anomalies are detected in a time-series graph.
    The algorithm's name is Holt-Winters. The idea is simple, and the results are often useful.
    Cheers!
    00:00 What is a time series?
    00:30 How can we find anomalies?
    01:00 Anomaly Detection Algorithm
    02:25 Repeated Differentiation
    03:36 Example
    04:14 Thank you!
    #anomalydetection #timeseries #monitoring
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Комментарии • 8

  • @GautamKhatter
    @GautamKhatter 7 месяцев назад +2

    Amazing how high school mathematics is solving real business problems.

  • @asrjy
    @asrjy 7 месяцев назад +2

    Great video! I have a question. Why does 25-34 in the third graph show anomalies but in the original graph it seems normal?

  • @prasenlonikar9753
    @prasenlonikar9753 7 месяцев назад +2

    Gaurav, you have very well explained here.
    I have a question - let's say i want to predict anomalies. I know how to detect them,
    How would you do it ?

    • @gkcs
      @gkcs  7 месяцев назад +6

      Predicting is a bit impossible, no? It won't be an "anomaly" if it is an "expected event".

  • @mohinicoder
    @mohinicoder 7 месяцев назад

    I did this in my 2nd job at startup. Using derivative we were identifying spikes

  • @KomalYadav-di3qz
    @KomalYadav-di3qz 7 месяцев назад

    Easy peasy lemon squeeze. Thanks

  • @J0Y22
    @J0Y22 5 месяцев назад

    So how you will imply this?

  • @RishiRajxtrim
    @RishiRajxtrim 7 месяцев назад

    👍🙏💯