Machine Learning, Linear Regression, Ridge Regression, Lasso Regression, Genomics.
Underfitting is when a model can’t accurately capture the dependencies between dependent and independent variables. In general, this because the model is too simple or it got caught in a local minimum. Generally, you notice a low R2 with known data and poor capabilities to generalize with unseen