A General Framework for Dimensionality-Reducing Data Visualization Mapping

@article{Bunte2012AGF,
  title={A General Framework for Dimensionality-Reducing Data Visualization Mapping},
  author={Kerstin Bunte and Michael Biehl and Barbara Hammer},
  journal={Neural Computation},
  year={2012},
  volume={24},
  pages={771-804}
}
In recent years, a wealth of dimension-reduction techniques for data visualization and preprocessing has been established. Nonparametric methods require additional effort for out-of-sample extensions, because they provide only a mapping of a given finite set of points. In this letter, we propose a general view on nonparametric dimension reduction based on the concept of cost functions and properties of the data. Based on this general principle, we transfer nonparametric dimension reduction to… CONTINUE READING
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