clasiffication accuracy

I have red all post concerning the issue but I can’t find the answer. in file generated by option “Evaluate classifier” we have “Total samples = 10000” ot less
for classification process default is: 5000
So 5000 is for training and 5000 others for validation? if possible so if there are enough amount of the pixels?
An it is randomly taken in each approach.
Am I right?
thanks in advance

Maybe the Help from SNAP can answer to your questions?

Best regards,

I thought so, but it confused me

Using Testing dataset, % correct predictions = 78.5099
Total samples = 10000
RMSE = 2.58785157342389
Bias = -0.028840376527138112

Using Testing dataset, % correct predictions = 70.9562
Total samples = 8952
RMSE = 2.949795891213707
Bias = -0.7924486148346741
in this case probably there was no enough pixels