  In statistics, researchers use Regression models for data analysis and
prediction in many productive sectors (industry, business, academy, etc.).
Regression models are mathematical functions representing an approximation of
dependent variable $Y$ from n independent variables $X_i \in X$. The literature
presents many regression methods divided into single and multiple regressions.
There are several procedures to generate regression models and sets of
commercial and academic tools that implement these procedures. This work
presents one open-source program called Regressor that makes models from a
specific variation of polynomial regression. These models relate the
independent variables to generate an approximation of the original output
dependent data. In many tests, Regressor was able to build models five times
more accurate than commercial tools.
