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Regularization In Machine Learning.
Regularization In Machine Learning Table Of Contents: What Is Regularization? Types Of Regularization Techniques. L1 Regularization (Lasso Regularization). L2 Regularization (Ridge Regularization). Elastic Net Regularization. (1) What Is Regularization? Regularization in machine learning is a technique used to prevent overfitting and improve the generalization performance of a model. Overfitting occurs when a model learns to fit the training data too closely, capturing noise or irrelevant patterns that do not generalize well to new, unseen data. Regularization introduces additional constraints or penalties to the learning process to prevent the model from becoming too complex or sensitive to the training data. (2)
