KawaiiCakes3937 KawaiiCakes3937
  • 27-07-2022
  • Mathematics
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When training models, you would typically place your data into three buckets: Train, Test, and Hold Out. What is the purpose of having hold-out data

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TeAL146
TeAL146 TeAL146
  • 27-07-2022

Answer:

So, having "hold-out" data allows you to have a nonpartisan set of data (so to speak) for you to refer to later, once you have made use of the "train" and "test" sets. That way you can make a fair assessment as to the difference between the new and old ('hold-out") sets.

Or if you need to repeat the experiment or model again - then you can refer to the "hold out data"

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