When high bias error exists, the model:

A. performs well on the training dataset but not on the CV dataset.
B. performs well on the CV datasets but not on the training dataset.
C. does not perform well on either training or CV dataset.

Correct Answer: C

Bias is the difference between the average prediction of our model and the correct value which we are trying to predict. Model with high bias pays very little attention to the training data and oversimplifies the model. It always leads to high error on training and test data. The model is typically lacking important predictor variables.