This article proposes an algorithm for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The resulting ...

Application: support vector machines regression algorithms has found several applications in the oil and gas industry, classification of images and text and hypertext categorization. In the oilfields, ...

The optimization approach based on the genetic algorithm (GA) combined with multiple linear regression (MLR) method, is discussed. The GA-MLR optimizer is designed for the nonlinear least-squares ...

Gradient boosted decision tree is a supervised learning algorithm model constructed by improving tree structure, replacing residual with gradient and using the concept of entropy in informatics. GBDT ...

Application of Regression Analysis in Business. ... which makes it a non-linear regression. For example: MS Growth= 1/2 (Square root of GDP Growth). ...

Looking at the three common types of regression algorithms that you really ... #1 Linear regression. ... Agentic AI applications for data engineering and data science along with a new underlying ...

Linear regression algorithms fit a straight line, or another function that is linear in ... Martin is the author or co-author of nearly a dozen PC software packages and half a dozen Web applications.

We introduce a randomized algorithm for overdetermined linear least-squares regression. Given an arbitrary full-rank m × n matrix A with m ≥ n, any m × 1 vector b, and any positive real number ε, the ...