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Nonlinear Dimensionality Reduction (Information Science and Statistics) by John A. Lee; Michel Verleysen is a mathematics available to read on EtoBox.
What is Nonlinear Dimensionality Reduction (Information Science and Statistics) about?
<p>Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able to reduce the data dimensionality in a nonlinear way. However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, ha
Who reads Nonlinear Dimensionality Reduction (Information Science and Statistics)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- John A. Lee; Michel Verleysen
- Publisher
- Springer New York
- Published
- 2007
- Language
- EN
- ISBN
- 9780387393506
- Category
- mathematics
- Subjects
- Mathematics, Management & Leadership, Logic
- Updated
- 2026-03-24
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