What are the different types of regularization in machine learning?
An example of an AI chatbot conversation about types of regularization in machine learning.
What are the different types of regularization in machine learning?
Regularization techniques help prevent overfitting in models. Common types include L1, L2, and Elastic Net.
Can you explain L1 regularization?
L1 regularization, also known as Lasso, adds a penalty equal to the absolute value of the coefficients, promoting sparsity.
What about L2 regularization?
L2 regularization, or Ridge, adds a penalty equal to the square of the coefficients, which helps to reduce model complexity.
When should I use Elastic Net?
Elastic Net combines L1 and L2 regularization, making it useful when you have many correlated features.
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