Performance regression testing is a method of comparing how a software programme performs over time in different builds. Simply put, performance regression testing offers information on how the application's performance changes as a result of recent development modifications.
Regression analysis is a collection of machine learning algorithms for predicting a continuous outcome variable (y) based on the values of one or more predictor variables (x). In a nutshell, the purpose of a regression model is to create a mathematical equation that specifies y as a function of x variables.
Regrettably, this is where the parallels between regression and classification machine learning end. The fundamental distinction is that in regression, the output variable is numerical (or continuous), whereas in classification, it is categorical (or discrete).
Regression is a method for modelling and analysing the relationships between variables, as well as how they contribute to and are connected to obtaining a specific outcome. A regression model with only linear variables is referred to as a linear regression.