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AI & Machine Learning · Foundational

Underfitting

When a model is too simple to capture underlying patterns and performs poorly on both training and new data.

Definition

Underfitting reflects high bias: the model cannot represent the relationship between features and target. Remedies include a more complex model, more or better features, less regularization or longer training.

Example

Fitting a straight line to clearly curved data.

Exam tip

Poor training and poor validation performance together indicate underfitting, not overfitting.

Don't confuse it with

Related terms