Predictive Modelling for Future Technology Development

doi:10.4018/978-1-7998-8327-2.ch027

Paper

Predictive Modelling for Future Technology Development

Published Jan 1, 2021 · Preeti Bala

Handbook of Research on Future Opportunities for Technology Management Education

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Abstract

The prediction models in machine learning and the application of different algorithms help in developing appropriate knowledge of future behaviour based on past data. With a view to help developing insights, this chapter explains the basics of predictive analytics with its common traits. The main objective of this chapter and the topics covered in the predictive models show how different methods of tools and algorithms are crucial for predictive analytics and steps to be used to make a good model. It also describes the basic tools and techniques to be used in predictive modelling. The discussions are based on the data of live projects in predictive modelling. It attempts to handle the predictive analytics like linear regression, multivariate linear regression, nonlinear regression, and multivariate non-linear regression. These statistical tools are crucial and critical in future technology developments.

Study Snapshot

Predictive modeling in machine learning helps develop insights into future behavior based on past data, aiding future technology development.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Predictive Modelling for Future Technology Development

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