The article explores using polynomial equations for regression instead of the usual linear or piecewise models. The researchers developed a method called Ciper to create these polynomial equations and tested them on standard regression tasks. They found that the polynomial models performed better in terms of accuracy and simplicity compared to other methods. Additionally, the polynomial models had lower variability in their predictions than regression tree methods.