Exploring the within- and between-class correlation distributions for tumor classification.

@article{Wei2010ExploringTW,
  title={Exploring the within- and between-class correlation distributions for tumor classification.},
  author={Xuelian Wei and Ker-Chau Li},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  year={2010},
  volume={107 15},
  pages={
          6737-42
        }
}
To many biomedical researchers, effective tumor classification methods such as the support vector machine often appear like a black box not only because the procedures are complex but also because the required specifications, such as the choice of a kernel function, suffer from a clear guidance either mathematically or biologically. As commonly observed, samples within the same tumor class tend to be more similar in gene expression than samples from different tumor classes. But can this well… CONTINUE READING

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