Domain adaptation
id:
domain-adaptation-243-7897881
title:
Domain adaptation
text:
Domain adaptation is a field associated with machine learning and transfer learning. This scenario arises when we aim at learning a model from a source data distribution and applying that model on a different target data distribution. For instance, one of the tasks of the common spam filtering problem consists in adapting a model from one user to a new user who receives significantly different emails. Domain adaptation has also been shown to be beneficial to learning unrelated sources.
Note that
brand slug:
wiki
category slug:
encyclopedia
description:
Field associated with machine learning and transfer learning
original url:
https://en.wikipedia.org/wiki/Domain_adaptation
date created:
date modified:
2024-04-03T06:12:56Z
main entity:
{"identifier":"Q19246213","url":"https://www.wikidata.org/entity/Q19246213"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/1/11/Transfer_learning_and_domain_adaptation.png","width":1257,"height":763}
fields total:
13
integrity:
15