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Table 2 Classification results observed by cross validation using SVM classifiers. Figures represent achieved classification accuracies, i.e. the fraction of samples correctly classified. The upper table shows results for cross validation analysis of both data sets of a pair, where samples for training and testing are selected randomly from both studies. For this, data sets were integrated by either MRS or QD. The bottom table contains the results of a cross-validated classification analysis performed separately on each study, using all available gene expression data after pre-processing (without applying MRS or QD). Abbreviations: MRS, median rank scores; QD, quantile discretization, SVM, support vector machine.

From: Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

both data sets integrated   
  MRS QD
Prostate cancer 97.67 % 97.56 %
Breast cancer 87.01 % 88.97 %
Acute myeloid leukemia 90.60 % 90.20%
original data   
Prostate cancer Dhanasekaran et al. Welsh et al.
  95.28 % 99.09 %
Breast cancer Gruvberger et al. West et al.
  80.52 % 86.73 %
Acute myeloid leukemia Bullinger et al. Valk et al.
  68.53 % 99.90 %