Yoti blog

Why testing data is as important as training data for machine learning models

When developing machine learning systems for facial age estimation, the conversation often centres on the training data: how much you have, how diverse it is, how inclusive it is, and how well it represents your end users.  Not to mention, where the data comes from.  Intuitively, that focus makes sense. More data presumably leads to better models. But test data is just as important, and in some ways, even more critical for ensuring models perform effectively. Training data: more isn’t always better Common sense would suggest that for a machine learning model “the more data, the better.” And that’s