Classification using partial least squares with penalized logistic regression

@article{Fort2005ClassificationUP,
  title={Classification using partial least squares with penalized logistic regression},
  author={Gersende Fort and Sophie Lambert-Lacroix},
  journal={Bioinformatics},
  year={2005},
  volume={21 7},
  pages={
          1104-11
        }
}
MOTIVATION One important aspect of data-mining of microarray data is to discover the molecular variation among cancers. In microarray studies, the number n of samples is relatively small compared to the number p of genes per sample (usually in thousands). It is known that standard statistical methods in classification are efficient (i.e. in the present case, yield successful classifiers) particularly when n is (far) larger than p. This naturally calls for the use of a dimension reduction… CONTINUE READING

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