Which of the following is true about bias and variance?

Here you will find the answers of “Which of the following is true about bias and variance?“. This question is a part ” Machine Learning With R ”

Question: When building a decision tree, we want to split the nodes in a way that decreases entropy and increases information gain.

1. Having a high bias underfits the data and produces a model that is overly complex, while having high variance overfits the data and produces a model that is overly generalized.
2. Having a high bias underfits the data and produces a model that is overly generalized, while having high variance overfits the data and produces a model that is overly complex.
3. Having a high bias overfits the data and produces a model that is overly complex, while having high variance underfits the data and produces a model that is overly generalized.
4. Having a high bias overfits the data and produces a model that is overly generalized, while having high variance underfits the data and produces a model that is overly complex.

Correct Answer: 2

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