What is the role of regularization in machine learning models?
An example of an AI chatbot conversation about the importance of regularization in machine learning models.
What is the role of regularization in machine learning models?
Regularization helps prevent overfitting by adding a penalty to the loss function, encouraging simpler models.
Can you explain the different types of regularization techniques?
Sure! The most common types are L1 (Lasso) and L2 (Ridge) regularization, each with unique properties.
How do I choose the right regularization technique for my model?
It depends on your data and model. L1 can lead to sparse models, while L2 is better for multicollinearity.
What are the consequences of not using regularization?
Without regularization, models may fit noise in the training data, leading to poor generalization on unseen data.
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