Linear regression

Linear model

Statistics

Proper linear model

Local regression

Cross-sectional regression

Computer science

Regression analysis

Bayesian multivariate linear regression

Multivariate adaptive regression splines

Linear predictor function

Regression

Mathematics

Simple linear regression

Artificial intelligence

Regression diagnostic

Polynomial regression

Machine learning

Journal of Applied Science and Technology Trends

Perhaps one of the most common and comprehensive statistical and machine learning algorithms are linear regression. Linear regression is used to find a linear relationship between one or more predictors. The linear regression has two types: simple regression and multiple regression (MLR). This paper discusses various works by different researchers on linear regression and polynomial regression and compares their performance using the best approach to optimize prediction and precision. Almost all of the articles analyzed in this review is focused on datasets; in order to determine a model's efficiency, it must be correlated with the actual values obtained for the explanatory variables.

A Review on Linear Regression Comprehensive in Machine Learning