What is underfitting in machine learning?

Experience Level: Junior
Tags: Machine learning


Underfitting is the opposite of overfitting and occurs when a model is too simple to capture the underlying patterns in the training data. This results in a model that has high bias and low variance, and it performs poorly on both the training and test data. Underfitting can be addressed by increasing the model complexity or by collecting more training data.
Machine learning for beginners
Machine learning for beginners

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