Sliced Coordinate Analysis for Effective Dimension Reduction and Nonlinear Extensions

@inproceedings{Zhang2008SlicedCA,
  title={Sliced Coordinate Analysis for Effective Dimension Reduction and Nonlinear Extensions},
  author={Zhihua Zhang and Dit Yan Yeung and J. Tin-Yau Kwok and Edward Y. Chang},
  year={2008}
}
Sliced inverse regression (SIR) is an important method for reducing the dimensionality of input variables. Its goal is to estimate the effective dimension reduction directions. In classification settings, SIR is closely related to Fisher discriminant analysis. Motivated by reproducing kernel theory, we propose a notion of nonlinear effective dimension reduction and develop a nonlinear extension of SIR called kernel SIR (KSIR). Both SIR and KSIR are based on principal component analysis… CONTINUE READING

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