Machine learning approaches
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.
Publication Title
Dimensionality Reduction in Data Science
Recommended Citation
Venugopal, D., & Garzon, M. (2022). Machine learning approaches. Dimensionality Reduction in Data Science, 179-197. https://doi.org/10.1007/978-3-031-05371-9_9
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