



What is the effect of the regularization parameter (lambda or alpha)?
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what is overfitting Informational
- How can cross-validation be used to select the optimal kernel and regularization parameter for an SVM?
- How can data augmentation be used to reduce overfitting when training neural networks on image or text data?
- How does the regularization parameter in Ridge and Lasso affect the model and its tendency to overfit?
- What is the role of human expertise in identifying and mitigating overfitting?
- How can techniques like rolling window validation help in assessing overfitting in time series?
- How can the encoding of categorical features impact overfitting?
- What are the trade-offs between different overfitting reduction techniques in terms of computational cost and performance?
- What strategies can be employed to address overfitting once it has been detected in a machine learning model?
- How does setting a minimum number of samples required at a leaf node help prevent overfitting?
- Describe how feature selection techniques can help in mitigating overfitting by reducing the complexity of the model and focusing on the most relevant features.
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