Underfitting

A concept in machine learning in which a model fails to fully capture the complexity of its training data. This may result in poor predictive ability and inaccurate outputs. Factors leading to underfitting may include having too few model parameters, having too high a regularization rate, or using an inappropriate or insufficient set of features in the training data.