Regularization: Difference between revisions
Thakshashila (talk | contribs) Created page with "= Regularization = '''Regularization''' is a technique in machine learning used to prevent '''overfitting''' by adding extra constraints or penalties to a model during training. == Why Regularization is Important == Overfitting happens when a model learns noise and details from the training data, harming its ability to generalize on new data. Regularization discourages overly complex models by penalizing large or unnecessary model parameters. == Common Types of Regul..." |
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regularization in machine learning, l1 regularization, l2 regularization, preventing overfitting, ridge regression, lasso regression, elastic net, model generalization, penalty methods in ML | regularization in machine learning, l1 regularization, l2 regularization, preventing overfitting, ridge regression, lasso regression, elastic net, model generalization, penalty methods in ML | ||
[[Category:Artificial Intelligence]] | |||