Nomenclature for known individuals vs possibly same individuals
$begingroup$
What is the standard machine learning term for these two concepts?
- An "known" individual, from an essentially static collection of individuals
- 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
New contributor
$endgroup$
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$begingroup$
What is the standard machine learning term for these two concepts?
- An "known" individual, from an essentially static collection of individuals
- 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
New contributor
$endgroup$
add a comment |
$begingroup$
What is the standard machine learning term for these two concepts?
- An "known" individual, from an essentially static collection of individuals
- 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
New contributor
$endgroup$
What is the standard machine learning term for these two concepts?
- An "known" individual, from an essentially static collection of individuals
- 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
machine-learning
New contributor
New contributor
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