| Issue |
EPJ Web Conf.
Volume 376, 2026
6th International Conference on Recent Advances in Mechanical Engineering and Nanomaterials (ICRAMEN 2026)
|
|
|---|---|---|
| Article Number | 06001 | |
| Number of page(s) | 11 | |
| Section | Recent Advances in Science & Engineering | |
| DOI | https://doi.org/10.1051/epjconf/202637606001 | |
| Published online | 01 July 2026 | |
https://doi.org/10.1051/epjconf/202637606001
Exploring Regression Models: Applications and Purposes of Linear, Logistic, and Polynomial Approaches in Engineering and Technologies
Department of Mathematics, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune-18, Maharashtra, India.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 1 July 2026
Abstract
Regression analysis is a vital data-driven technique for examining variable relationships and predicting outcomes. It allows researchers to identify how independent variables influence a dependent variable, enabling predictions, trend analysis, and decision-making across various fields. This paper provides a comprehensive overview of regression techniques, which includes simple and multiple linear regression as well as logistic and polynomial regression models. Each technique is explained with its assumption, mathematical formulation, and use cases. The study also highlights the strengths and limitations of each model. This work aims to gain a deeper understanding of regression analysis and its practical application in real-world datasets. This also examines their applications in the field of modern engineering and machine learning.
Key words: Regression models / Linear regression / Multilinear regression / Logistic regression / Polynomial regressions with examples / Comparative study
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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