Regression predictive modeling (or just regression) is the problem of learning the strength of association between independent variables (or features) and continuous dependent variables (or outcomes). Tuning regression algorithms is similar to tuning classification algorithms. That is, we adjust a model’s hyperparameters until we arrive at an optimal solution.
The difference is that the goal of regression tuning is to reduce root mean squared error (RMSE), while the goal of classification tuning is to maximize accuracy. A benefit of RMSE is that units of the ...
