Quantization and distance function selection for discrimination of tumors using gene expression data

摘要

This paper compares several discrimination methods for the classification of tumors using gene expression data. We introduce variations of known classification methods, and compare the effects of quantizing the data prior to applying various methods, and also discuss the selection of the distance function. The error rates obtained with the new methods are shown to be smaller than those reported in recently published studies.