Machine Learning, Model Selection, Hyperparameter Tuning, Learning Curve, Cross Validation.
low bias if the training score plateaus at a high level while the validation score at a low level, i.e., if there is a large gap between training and validation score. A model with low variance but high bias, in contrast, is a model where both training and validation score are low, but similar.