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Related Questions
- What are the main types of regularization techniques used in machine learning, and how do they impact model capacity?
- How does model capacity affect the trade-off between overfitting and underfitting, and how can regularization techniques help?
- Can you explain the concept of overfitting and how regularization techniques can prevent it?
- How do different regularization techniques, such as L1 and L2 regularization, affect model capacity and generalization?
- What is the relationship between model capacity and the risk of overfitting, and how can regularization techniques mitigate this risk?
- Can you describe how dropout regularization affects model capacity and generalization, and how it can be used to prevent overfitting?
- How do ensemble methods, such as bagging and boosting, interact with model capacity to improve generalization and prevent overfitting?
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