Corpus ID: 60729688

Nonlinear Dimensionality Reduction

@inproceedings{Lee2007NonlinearDR,
  title={Nonlinear Dimensionality Reduction},
  author={John Aldo Lee and Michel Verleysen},
  year={2007}
}
  • John Aldo Lee, Michel Verleysen
  • Published 2007
  • Computer Science
  • 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, has… CONTINUE READING

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