validation sets vs test sets
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Seemab Janjua
el 16 de Dic. de 2015
Respondida: Greg Heath
el 17 de Dic. de 2015
what is difference between validation and test datasets ?
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Sean de Wolski
el 16 de Dic. de 2015
I assume you're talking about Neural Networks?
If so, validation is used for the neural network to decide when training is complete and to avoid overfitting. Testing is an independent test set.
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Greg Heath
el 17 de Dic. de 2015
Total = Design + Nondesign
Design = Training + Validation
Nondesign = Testing
Total = Training + Nontraining
Nontraining = Validation + Testing
Overfitting: Using more weights and biases than necessary
Overtraining: Improving the performance of the training data at the expense of deteriorating the performance
on nontraining data
Training data subset: Used to DIRECTLY estimate weights and biases. Performance estimates are BIASED.
Validation data subset: Used to
(1) determine when overtraining an overfit net begins to occur AND
(2) rank multiple designs.
Performance estimates are SIGNIFICANTLY LESS BIASED than training data estimates.
Test data subset: Used to obtain UNBIASED ESTIMATES of performance on nontraining (INCLUDING UNSEEN!) data
HOPE THIS HELPS
GREG
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