Application of Regression in Data Mining

20 Pages Posted: 25 Nov 2020 Last revised: 7 Jan 2021

See all articles by Nithya P

Nithya P

Pondicherry University

Elavarasan G

Pondicherry University

Kadhiravan N

Pondicherry University

Priyadharshini S

Pondicherry University

Amudha Adhirai A

Pondicherry University

Date Written: November 20, 2020

Abstract

Regression is one of a data mining technique which is used to anticipate a range of continuous values(numeric) for a given data set. In other words, regression is used to observe the cost of a product or service from given other variables. It is widely used in business marketing, financial & trend forecasting, modelling of environment and so on. Classification is also similar to regression but it is used to predict a discrete set of values not continuous. Regression is used at the situation when the output is a continuous value like salary, weight, height etc. A kind of demographic activity for evaluating the interrelation between the subordinate variables and more than one absolute variables(predictors) is known as regression analysis which helps us to know how much the value of the subordinate variable is varying by the independent variable. The key terms involved in regression are dependent & independent variable, outliers, multicollinearity, underfitting and overfitting. In this paper, the regression concepts are going to be discussed and various kinds of regression techniques available and their uses in the real world. The main desire is to clear about the regression concept and its importance in this paper.

Keywords: Kinds of regression, Predictor variable, Forward selection, Supervised classification, Penalty function.

Suggested Citation

P, Nithya and G, Elavarasan and N, Kadhiravan and S, Priyadharshini and A, Amudha Adhirai, Application of Regression in Data Mining (November 20, 2020). Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), Available at SSRN: https://ssrn.com/abstract=3734277 or http://dx.doi.org/10.2139/ssrn.3734277

Nithya P (Contact Author)

Pondicherry University ( email )

Mahe Centre, Cemetery Road
Pondicherry, Puducherry UT 605 014
India

Elavarasan G

Pondicherry University ( email )

Mahe Centre, Cemetery Road
Pondicherry, Puducherry UT 605 014
India

Kadhiravan N

Pondicherry University ( email )

Mahe Centre, Cemetery Road
Pondicherry, Puducherry UT 605 014
India

Priyadharshini S

Pondicherry University ( email )

Mahe Centre, Cemetery Road
Pondicherry, Puducherry UT 605 014
India

Amudha Adhirai A

Pondicherry University ( email )

Mahe Centre, Cemetery Road
Pondicherry, Puducherry UT 605 014
India

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
18
Abstract Views
106
PlumX Metrics