Sentence examples for linear regression regression from inspiring English sources

The models evaluated were linear regression, regression trees and ordinary and regression kriging.

Authors like Alberto Gonzalez-Sanchez, Juan Frausto-Solis Frausto-Solis and Waldo Ojeda-Bustamante Ojeda-Bustamanteredictive ability of machave learning techniques such as multiple linear regression, regression trees, artificial neural network, support vector regression andonenextensiveighbour for crop yield production [12].

After evaluating the assumptions for linear regression, regression was used to analyze the relationship of LOS and all predictor variables.

Various prediction methods have been tested (multiple linear regression, regression-based trees, bagging, and additive regression) using different features extracted from the news web platform.

Section IV provides a brief theoretical overview of some machine learning techniques which are regressive predictive algorithms including: Decision Tree Regression, Multiple Linear Regression and Support Vector Regression.

These include generalized linear models, quantile regression, nonlinear regression, and generalized additive models.

Data were analysed using linear regression and logistic regression models.

He listed seven types of regression models as linear regression, logistic regression, polynomial regression, stepwise regression, ridge regression, Lasso regression, elastic net regression.

Support Vector Machines: Support Vector Machine implementation using the LibSVM library [23].... two workers do only support regression... Multiple Linear Regression: Multiple linear regression algorithm.

A comparison between multiple linear regression and regression trees showed that the tree model yielded the best results.

Multiple linear regression, principal component regression and partial least squares were used as the regression methods.