Parametric methods are those that attempt to estimate the parameters of a model. For example, in [[base/Linear Regression/linear regression|linear regression]], we attempt to estimate the values of $p + 1$ parameters $\beta_0, \beta_1, \dots, \beta_p$. Parametric methods require us to first make an assumption about the functional form of the model (e.g., the function $f$ is linear). Next, we find a procedure to use the training data to fit or train the model. Contrast with non-parametric methods like [[nonparametric regression]].