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Early Stopping

Early Stopping is a form of regularization used to avoid overfitting when training a learner with an iterative method such as gradient descent (GD). If your model learns your training data โ€œtoo wellโ€, it will be counterproductive. This is because the model will be incorporating too much of the noise features, rather than the important ones. You should stop the training before the generalization error gets too high.

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