What are some other types of regularization in machine learning?
An example of an AI chatbot conversation about other types of regularization in machine learning.
What are some other types of regularization in machine learning?
In addition to L1 and L2 regularization, there are several other types, such as dropout, early stopping, and data augmentation.
Can you explain dropout regularization?
Dropout is a technique where randomly selected neurons are ignored during training, which helps prevent overfitting.
What is early stopping?
Early stopping involves monitoring the model's performance on a validation set and halting training when performance starts to degrade.
How does data augmentation help with regularization?
Data augmentation increases the diversity of your training set by applying transformations, which helps the model generalize better.
Are there any other techniques I should know about?
Yes, techniques like batch normalization and weight decay are also important for regularization in machine learning.
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