Evaluating Synthetic Data using Machine Learning

Evaluating Synthetic Data Using Machine Learning

Adversarial validation to evaluate synthetic data

“Poor accuracy score” is a phrase that might cause nightmares for many data science professionals when building machine learning models for classification problems. However, a poor accuracy score can be a blessing in rare scenarios, especially when performing adversarial validation.

Adversarial validation is conducted to evaluate if two datasets come from the same distribution or not. Generally, it is used to measure data shifts in training and …

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