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Related Questions
- What are the common pitfalls of neural networks when dealing with out-of-distribution inputs?
- How do decision trees handle uncertainty and ambiguity in out-of-distribution inputs?
- What are the key differences in how neural networks and decision trees handle out-of-distribution inputs?
- Can you explain the concept of inductive bias and how it affects a model's performance on out-of-distribution inputs?
- How do ensemble methods, such as bagging and boosting, handle out-of-distribution inputs?
- What is the role of regularization techniques, such as L1 and L2 regularization, in preventing overfitting on out-of-distribution inputs?
- Can you discuss the trade-offs between model complexity and interpretability when handling out-of-distribution inputs?
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