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Which method is frequently used to prevent overfitting?
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Answer / Rajesh Mathpal
There are several methods for preventing overfitting in machine learning. One common approach is Regularization, which adds a penalty term to the loss function to reduce the complexity of the model and encourage simpler solutions. Another popular technique is Cross-Validation, where the dataset is divided into multiple folds, and the model's performance is evaluated on each fold in turn.
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