You are asked several ML theory questions:
-
Bagging vs. boosting
-
What is the difference between bagging and boosting?
-
When would you prefer one over the other?
-
Random forest
-
What is a random forest?
-
How does it relate to bagging and decision trees?
-
Bias–variance tradeoff
-
Define bias and variance.
-
How do bagging/boosting/random forests typically affect bias and variance?
-
What common symptoms would you observe (e.g., underfitting/overfitting) and how would you mitigate them?