Titlebook: Elements of Dimensionality Reduction and Manifold Learning; Benyamin Ghojogh,Mark Crowley,Ali Ghodsi Textbook 2023 The Editor(s) (if appli

SNEER

Sufficient Dimension Reduction and Kernel Dimension ReductionSuppose there is a dataset that has labels, either for regression or classification. Sufficient Dimension Reduction (SDR), first proposed by Li, is a family of methods that find a transformation of the data to a lower dimensional space, which does not change the conditional of labels given the data.

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978-3-031-10604-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Benyamin Ghojogh,Mark Crowley,Ali GhodsiExplains the theory of fundamental algorithms in dimensionality reduction, in a step-by-step and very detailed approach.Useful for anyone who wants to understand the ways to extract, transform, and un

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,L’adolescent, la mère et l’enfant,cipal Component Analysis (PCA) (see Chap. .) and Fisher Discriminant Analysis (FDA) (see Chap. .), learn a projection matrix for either better representation of data or discrimination between the classes in the subspace.

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https://doi.org/10.1007/978-3-031-10602-6Data Reduction; Data Visualization; Dimensionality Reduction; Feature Extraction; Machine Learning; Manif