机器学习中Training, Validation 和 Test 集合之间的区别
机器学习中Training, Validation 和 Test 集合之间的区别
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Mostly, we divide the whole set into 3 parts.
1. Training Set
Train your model. You can optimize your model, change some parameters and so on.
2. Validation Set
Look at your models and select the best performing approach using the validation data. Compare your algorithms and their training parameters and decide on a winner.
3. Test Set
Do not change any parameters, just test your winner model
Reference
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