When talking about the bias$/$variance tradeoff, what is the $$bias$?$

Answer

a$.$

The tendency of a model to overfit

b$.$

When the expected error is large across multiple training data samples

c$.$

The minimum error of any model from a hypothesis class

d$.$

When the model is prone to biases in the training data