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How to measure the performance of a domain adaptation /Transfer learning technique?



The 2019 Stack Overflow Developer Survey Results Are InTraining data from different sourcesDiscrepancy between training set and real-world data set: domain adaptation?Transfer learning: Poor performance with last layer replacedDomain adaption vs. heirarchical model - when to use which?What is in-domain and out-domain exactly in language model and How can we distinguish in-domain and out-of-domain data?correcting conditional and marginal distribution in transfer learningResource and useful tips on Transfer Learning in NLPNon-Compact Domain/Range Machine LearningOver fitting in Transfer Learning with small datasetWhy do I need pre-trained weights in transfer learning?










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Given that the performance you achieve depends on how far the target from the source domain is, how can you judge the performance of an algorithm?










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    Given that the performance you achieve depends on how far the target from the source domain is, how can you judge the performance of an algorithm?










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    $endgroup$














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      $begingroup$


      Given that the performance you achieve depends on how far the target from the source domain is, how can you judge the performance of an algorithm?










      share|improve this question









      $endgroup$




      Given that the performance you achieve depends on how far the target from the source domain is, how can you judge the performance of an algorithm?







      machine-learning transfer-learning domain-adaptation






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