What is early stopping and how does it prevent overfitting?
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what is overfitting Informational
- How can analyzing the learning curves help you decide whether to add more data, increase model complexity, or try regularization techniques?
- How does the evaluation metric used affect our perception of overfitting?
- Consider a decision tree model. How does allowing the tree to grow too deep lead to overfitting?
- Consider the bias-variance trade-off. How do bagging and boosting typically affect the bias and variance of the resulting ensemble model compared to the individual base models?
- What are some techniques for estimating the uncertainty of model predictions?
- What are some techniques to prevent overfitting in logistic regression, similar to linear regression?
- What is knowledge distillation and how can it be used to transfer knowledge from a large, well-regularized model to a smaller, more efficient one?
- How can analyzing the feature importance scores of a model help in detecting potential overfitting to irrelevant or noisy features?
- How does the latent space dimensionality in VAEs affect overfitting?
- What are some promising new approaches for addressing the challenges of overfitting in increasingly complex models and datasets?
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