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AUTOMATIC CORRECTION OF INDIRECT BIAS IN MACHINE LEARNING MODELS

  • US 20200134493A1
  • Filed: 10/31/2018
  • Published: 04/30/2020
  • Est. Priority Date: 10/31/2018
  • Status: Active Grant
First Claim
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1. A computer-implemented method comprising:

  • receiving, by a computer device, a user request to detect transitive bias in a machine learning model;

    determining, by the computer device, correlations of attributes of neighboring data not included in a dataset of the machine learning model;

    ranking, by the computer device, the attributes based on the determined correlations; and

    returning, by the computer device, a list of the ranked attributes to a user that generated the user request.

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