TITLE:
Comparative Study of Probabilistic and Least-Squares Methods for Developing Predictive Models
AUTHORS:
Boribo Kikunda Philippe, Thierry Nsabimana, Jules Raymond Kala, Jeremie Ndikumagenge, Longin Ndayisaba
KEYWORDS:
Predictive Models, Least Squares, Bayesian Estimation Methods
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.14 No.7,
July
19,
2024
ABSTRACT: This article explores the comparison between the probability method and the least squares method in the design of linear predictive models. It points out that these two approaches have distinct theoretical foundations and can lead to varied or similar results in terms of precision and performance under certain assumptions. The article underlines the importance of comparing these two approaches to choose the one best suited to the context, available data and modeling objectives.