What is overfitting in machine learning?

Experience Level: Junior
Tags: Machine learning


Overfitting is a common problem in machine learning where a model learns the training data too well and fails to generalize to new, unseen data. This occurs when the model is too complex relative to the amount of training data, and it begins to memorize the noise or random variation in the training data. Overfitting can be addressed by using techniques such as regularization, early stopping, and cross-validation.
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