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UNSUPERVISED MACHINE LEARNING ENSEMBLE FOR ANOMALY DETECTION

  • US 20180096261A1
  • Filed: 10/01/2016
  • Published: 04/05/2018
  • Est. Priority Date: 10/01/2016
  • Status: Active Application
First Claim
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1. At least one machine accessible storage medium having instructions stored thereon, the instructions when executed on a machine, cause the machine to:

  • identify a collection of data, wherein the collection of data comprises data generated by a plurality of sensors;

    generate a set of feature vectors from the collection of data;

    execute a plurality of unsupervised anomaly detection machine learning algorithms in an ensemble using the set of feature vectors;

    generate a set of pseudo labels based on predictions made during execution of the plurality of unsupervised anomaly detection machine learning algorithms using the set of feature vectors; and

    execute a supervised machine learning algorithm using the set of pseudo labels as training data to determine an anomaly detection model corresponding to the plurality of sensors.

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