Implementation of Regression Analysis Using Regression Algorithms for Decision Making in Business Domains

K. Bhargavi and Ananthi Sheshasaayee
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K. Bhargavi: Quaid-E-Millath Government College for Women, PG & Research Department of Computer Science
Ananthi Sheshasaayee: Quaid-E-Millath Government College for Women, PG & Research Department of Computer Science

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 819-828 from Springer

Abstract: Abstract Decision making is a process of reaction against organizational hazards and opportunities. It includes the process of collecting and processing the information gathered and selecting the alternative from the set of alternatives based on their values using different tools, techniques, and insights. Regression analysis is one among the most dominant techniques used for decision making in business by the management. To make better decisions, regression analysis helps the managers to understand the data to model dependencies and helps to understand the relationship between the expected output and the input features to predict the values. The main application of regression analysis is to find how strong an independent variable influence the dependent variable. There are many areas where regression analysis can be applied in organizations for better prediction, mainly in financial forecasting, marketing, understanding inventory levels, supply chain, trend analysis, and time series prediction. In this paper, the application of regression analysis in different organizational decision making and the different types of regressions used in organizational decision making are discussed.

Keywords: Simple linear regression; Lasso regression; Logistic regression; Support vector machines; Multivariate regression; Multiple regression (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_82

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DOI: 10.1007/978-3-030-41862-5_82

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