Journal of Computer & Information Technology

Papers

Voulume: 8
Issue: 6
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Article No. 1
A comparative Analysis of Multiple Regression in Data Mining
PRIYANKA VERMA
M. Tech Scholar, Department of Computer Science & Engineering, Lakshmi Narain College of Technology & Excellence Bhopal (M.P), (India)
RAJNI KORI
Assistant Professor, Department of CSE, Lakshmi Narain College of Technology & Excellence, Bhopal (M.P), (India)
SHIV KUMAR3
Professor & Head, Department of CSE, Lakshmi Narain College of Technology & Excellence, Bhopal (M.P), (India)
Abstract :

The growing volume of data usually creates an interesting challenge for the need of data analysis tools that discover regularities in these data. Data mining has emerged as disciplines that contribute tools for data analysis, discovery of hidden knowledge, and autonomous decision making in many application domains. The Multiple regressions generally explain the relationship between multiple independent or multiple predictor variables and one dependent or criterion variable. The regression algorithm estimates the value of the target (response) as a function of the predictors for each case in the build data. These relationships between predictors and target are summarized in a model, which can then be applied to a different data set in which the target values are unknown.
In this paper, we have discussed the formulation of multiple regression technique, along with that multiple regression algorithm have been designed, further test data are taken to prove the multiple regression algorithm.

 

Keyword : Multiple regression, dependent variable, independent variables, predictor variable, response variable
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