Underfitting is another scenario where model performs badly. This is a phenomenon where the performance of the model is affected because the model is not well trained. Such systems have trouble in generalizing new data. 

For ideal model performance, both overfitting and underfitting can be prevented by performing some common machine learning procedures, like cross validation of the data, data pruning, and regularization of the data. We will go through these in much more detail in the following chapters after we get more acquainted with machine learning models.