Machine Learning Approaches

Deepak Venugopal () and Max Garzon ()
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Deepak Venugopal: The University of Memphis, Computer Science
Max Garzon: The University of Memphis, Computer Science

Chapter Chapter 9 in Dimensionality Reduction in Data Science, 2022, pp 179-197 from Springer

Abstract: Abstract Machine learning algorithms can train a model to extract some hidden patterns in a dataset to solve a problem or elucidate dependencies among the predictors and thus select or extract features that enable solutions to complex questions from large datasets. This chapter reviews various machine learning methods for dimensionality reduction, including autoencoders, neural networks themselves, and other methods.

Date: 2022
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DOI: 10.1007/978-3-031-05371-9_9

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