Nomenclature for known individuals vs possibly same individuals












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What is the standard machine learning term for these two concepts?




  1. An "known" individual, from an essentially static collection of individuals

  2. A "query" individual, which may "match" 0-n of the known individuals


Specific context:



The "known" items are a list of things that will be searched for, eg customers.

The "query" items are items with incomplete and/or erroneous feature data



Machine learning will be used to train a model to find all "known" items that have "similar" features (ie they "match"). As a trivial example would be the known items include "John Smith" and "Jon Smith" and a query item "John Smithe" should return both of those known items.



Are there industry standard terms for the 2 types of things?









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    $begingroup$


    What is the standard machine learning term for these two concepts?




    1. An "known" individual, from an essentially static collection of individuals

    2. A "query" individual, which may "match" 0-n of the known individuals


    Specific context:



    The "known" items are a list of things that will be searched for, eg customers.

    The "query" items are items with incomplete and/or erroneous feature data



    Machine learning will be used to train a model to find all "known" items that have "similar" features (ie they "match"). As a trivial example would be the known items include "John Smith" and "Jon Smith" and a query item "John Smithe" should return both of those known items.



    Are there industry standard terms for the 2 types of things?









    share







    New contributor




    Bohemian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















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      $begingroup$


      What is the standard machine learning term for these two concepts?




      1. An "known" individual, from an essentially static collection of individuals

      2. A "query" individual, which may "match" 0-n of the known individuals


      Specific context:



      The "known" items are a list of things that will be searched for, eg customers.

      The "query" items are items with incomplete and/or erroneous feature data



      Machine learning will be used to train a model to find all "known" items that have "similar" features (ie they "match"). As a trivial example would be the known items include "John Smith" and "Jon Smith" and a query item "John Smithe" should return both of those known items.



      Are there industry standard terms for the 2 types of things?









      share







      New contributor




      Bohemian is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      What is the standard machine learning term for these two concepts?




      1. An "known" individual, from an essentially static collection of individuals

      2. A "query" individual, which may "match" 0-n of the known individuals


      Specific context:



      The "known" items are a list of things that will be searched for, eg customers.

      The "query" items are items with incomplete and/or erroneous feature data



      Machine learning will be used to train a model to find all "known" items that have "similar" features (ie they "match"). As a trivial example would be the known items include "John Smith" and "Jon Smith" and a query item "John Smithe" should return both of those known items.



      Are there industry standard terms for the 2 types of things?







      machine-learning





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