Tailen Hsing

Learn More
Gene-expression-based classifiers suffer from the small number of microarrays usually available for classifier design. Hence, one is confronted with the dual problem of designing a classifier and estimating its error with only a small sample. Permutation testing has been recommended to assess the dependency of a designed classifier on the specific data set.(More)
Measuring the strength of dependence between two sets of random variables lies at the heart of many statistical problems, in particular, feature selection for pattern recognition. We believe that there are some basic desirable criteria for a measure of dependence not satisfied by many commonly employed measures, such as the correlation coefficient, Briefly(More)
  • 1