The adjusted R squared metric was designed to solve the previously described problem of the R squared metric. It is the same as the R squared metric but with a penalty for a large number of independent variables. The main idea is that if new independent variables improve the model's quality, the values of this metric increase; otherwise, they decrease. This can be given by the following equation:

Here, k is the number of parameters and n is the number of samples.