Search the World's Largest Database of Information Science & Technology Terms & Definitions
InfScipedia
A Free Service of IGI Global Publishing House
Below please find a list of definitions for the term that
you selected from multiple scholarly research resources.

# What is Regression

It is a statistical measure used to determine the strength of the relationship between one dependent variable and a series of other changing variables.
Published in Chapter:
Analysis of Cutting-Edge Regression Algorithms Used for Data Analysis
Indivar Mishra (KIIT University, India), Ritwik Bandyopadhyay (KIIT University, India), Sourish Ghosh (KIIT University, India), and Aleena Swetapadma (KIIT University, India)
DOI: 10.4018/978-1-5225-7277-0.ch011
Abstract
Considering the growing applications of big data analytics in the various fields such as healthcare, finance, e-commerce, and web services, it is essential to continuously develop techniques useful for big data. Among various techniques used for big data analytics, regression analysis is very important. In this chapter, an attempt is made to take a detailed look into some of the main regression algorithms and their origin that are used for big data analytics. In this study, some of very famous works related to regression along with some latest research are analyzed. Regression is the process of deducing a predictive model for real-world information based on verified information that is already received. It is used for making predictions, optimizing solutions to complex problems, and understands trends in large and big data analytics. The goal of this study is to promote and facilitate a better understanding of regression algorithms that are in use in the real world for big data analytics.
More Results
It is a statistical term concerning the analysis of relationship between different variables. Sensor: It is usually an electronic device taking a physical quantity as input and outputs an electronic signal which can be estimated and classified by human applications.
Regression analysis is a set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables.
It is a method used in machine learning to predict the relationship between independent and dependent variables.
A technique for determining the statistical relationship between two or more variables where a change in a dependent variable is associated with, and depends on, a change in one or more independent variables.
Fitting a model y = f ( x 1 , x 2 , …, x p ) + error relating the p predictors x 1 , x 2 , …, x p to the response y . If the function f is linear in the parameters, such as then the regression is a linear regression (even though it is not linear in the predictors x 1 and x 2 ).
A supervised learning task where the ground truth labels are real numbers.
A technique for determining the statistical relationship between two or more variables where a change in a dependent variable is associated with, and depends on, a change in one or more independent variables.
A measure of the relationship between the mean value of one variable (e.g., output) and corresponding values of other variables.
The most appropriate relationship between dependent variable(s) (Y) and independent variable(s) (X) is expressed as a mathematical function.
Regression is an approach that generates a model characterizing the relationship between independent and dependent factors of a system from sample data representing a certain observable fact.
Process to statistically estimate the relationship between different attributes.
It is a statistical approach to express the process response as a function of the process parameters.
It is a statistical approach to express the process response as a function of the process parameters.
A quantitative analysis that investigates the relationship between dependent and independent variables in data sets.
It is a supervised machine learning technique which is used to predict continuous values. Loss function is being calculated using Gradient Descent Algorithm.
A statistical technique that allows you to determine the mathematical relationship between one or more independent variables and a dependent variable. For example, given that car accidents increase in bad weather and on weekends and that bad weather tends to be more common on weekends, regression allows you to isolate the effect of accidents due to weekends alone.
Regression analysis is a statistical method that helps in analysing and understanding the relationship between two or more variables of interest.
A statistical method used in finance, investing, and other disciplines that attempts to determine the strength and character of the relationship between one dependent variable (usually denoted by Y) and a series of other variables (known as independent variables) (Beers, 2021).
Regression is another supervised learning task that discovers correlations between data features and predicts continuous-valued target output based on the historical data.
Itmodels the behavior of a quantitative variable (the target variable) based on various predictor variables (components or characteristics) that might be quantitative or qualitative.
A statistical process for determining the relation between one dependent variable and various other variables (also known as independent variables).
To comprehend which among the autonomous factors are related to the reliant factors, and regression analysis is used to investigate the forms of these connections. For instance, by utilizing a relapse (regression) model conceivable to predict kids' tallness, given their age, weight and different elements.
Will and mind suspension, spiritual backward linkage.
Regression analysis is a set of statistical processes for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables when the focus is on the relationship between a dependent variable and one or more independent variables (predictors).
The task of learning a target function that maps one or more input attributes to a single numeric attribute.
It is a method of projection of a dependent variable for a specific value of an independent variable. If y is dependent and x is independent variables with y* and x* as their mean values then the equation (y-y*) = b yx (x-x*) is called Regression Equation of y on x, where b yx is known as regression coefficient determined by variances of y and x and correlation coefficient. On the other hand the regression equation of x on y will be (x-x*) = b xy (y-y*), where b xy stands for the regression coefficient of x on y.
A method from machine learning predicting the relationship between independent and dependent variables.