underfitting
🤖 CT-AI
Official ISTQB Definition
A modeling error that occurs when a machine learning model is too simple to capture the underlying pattern in the data.
3 Ways to Think About It
The Quick Take
When an AI is too simple to capture the patterns in data - it performs poorly everywhere.
Look Closer
An ML model that hasn't learned enough, showing poor accuracy on both training and test data.
The Bottom Line
The opposite of overfitting: the model needs more complexity or training to be useful.
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