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One option is fingerprinting. If two objects have the same fingerprint, they are probably the same object. Depending the technique used, the fingerprint can not tell about approximate duplicates.


The reasoning will be: "The more data for training the better". Then you have to keep in mind that the validation/hold-out set has to resemble how it should work on production/testing. The theory is that the larger the training data, the better the model should generalize. The validation set can be much smaller, on extremely big dataset you can ...

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