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Data Mining and Knowledge Discovery

The goal is to discover precursors to adverse events/anomalies for which data leading up to the anomaly is available. An event may be defined as any combination of observed data at a given time stamp. Thus, a time series data (possibly multidimensional) may be considered as a sequence of events. By analyzing data from nominal and adverse time series data, we aim to identify precursor events and use the precursors for forecasting the adverse events.

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  • Discovery of Precursors to Adverse Events using Time Series Data

    A Publication, Discovering Precursors to Adverse Events in Time Series - 5 years, 3 months ago

    Shared By: Vijay Manikandan Janakiraman

    We develop an algorithm for automatic discovery of precursors in time series data (ADOPT). In a time series setting, a precursor may be considered as ...

    meatball
  • Identifying Precursors to Anomalies Using Inverse Reinforcement Learning

    A Publication, Discovering Precursors to Adverse Events in Time Series - 5 years, 6 months ago

    Shared By: Vijay Manikandan Janakiraman

    In this paper, we consider the problem of discovering candidate precursors to anomalies in a set of time sequenced data. Typical scenarios involving time sequential ...

    meatball

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Started: Mar 28, 2016

Last Activity: Mar 30, 2016

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