Regressor: A C program for Combinatorial Regressions

TL;DR

This paper introduces Regressor, an open-source C program for polynomial regression that significantly outperforms commercial tools in accuracy across various tests.

Contribution

The work presents Regressor, a novel open-source C implementation for a specific polynomial regression variation, enhancing model accuracy.

Findings

Regressor built models five times more accurate than commercial tools.

Demonstrated effectiveness across multiple tests.

Provides an accessible open-source tool for polynomial regression.

Abstract

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.