You're comparing a few supervised learning models and want to choose one that will generalize well to new data.
Explain the bias-variance tradeoff and how it impacts your choice of algorithm.
Understanding of bias versus varianceHow model complexity affects generalizationUse of regularization and cross-validationHow to choose between simpler and more flexible algorithms