Modern Statistical Modeling in Machine Learning and Big Data Analytics: Statistical Models for Continuous and Categorical Variables

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Author(s): Niloofar Ramezani (George Mason University, USA)
Copyright: 2022
Pages: 17
Source title: Research Anthology on Machine Learning Techniques, Methods, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6291-1.ch007

Keywords: Artificial Intelligence / Engineering Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Machine learning, big data, and high dimensional data are the topics we hear about frequently these days, and some even call them the wave of the future. Therefore, it is important to use appropriate statistical models, which have been established for many years, and their efficiency has already been evaluated to contribute into advancing machine learning, which is a relatively newer field of study. Different algorithms that can be used within machine learning, depending on the nature of the variables, are discussed, and appropriate statistical techniques for modeling them are presented in this chapter.

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Modern Statistical Modeling in Machine Learning and Big Data Analytics: Statistical Models for Continuous and Categorical Variables

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