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Table 2 Results of 16 datasets (16 binary classification tasks) using different data scaling algorithms and classification models

From: A robust data scaling algorithm to improve classification accuracies in biomedical data

dataset Method None Minmax Zscore GL
GSE27899IL LR NA ± NA NA ± NA NA ± NA NA ± NA
  SVM 0.768 ± 0.104 0.814 ± 0.084 0.814 ± 0.074 0.824 ± 0.058
Prostate Cancer LR 0.464 ± 0.000 0.749 ± 0.130 0.689 ± 0.156 0.761 ± 0.108
  SVM 0.573 ± 0.198 0.725 ± 0.232 0.713 ± 0.244 0.822 ± 0.194
Colon Cancer LR 0.500 ± 0.000 0.895 ± 0.092 0.892 ± 0.082 0.962 ± 0.046
  SVM 0.670 ± 0.184 0.940 ± 0.058 0.937 ± 0.050 0.981 ± 0.020
Lung Cancer LR 0.450 ± 0.000 0.839 ± 0.096 0.834 ± 0.108 0.890 ± 0.050
  SVM 0.397 ± 0.274 0.716 ± 0.136 0.710 ± 0.152 0.774 ± 0.182
Breast Cancer LR 0.324 ± 0.000 0.809 ± 0.038 0.821 ± 0.020 0.819 ± 0.022
  SVM 0.708 ± 0.158 0.793 ± 0.052 0.795 ± 0.042 0.812 ± 0.038
Leukemia LR 0.500 ± 0.000 0.988 ± 0.014 0.990 ± 0.006 1.000 ± 0.000
  SVM 0.935 ± 0.034 0.992 ± 0.010 0.991 ± 0.008 1.000 ± 0.000
GSE29490 LR NA ± NA NA ± NA NA ± NA NA ± NA
  SVM 0.983 ± 0.012 0.984 ± 0.034 0.985 ± 0.034 0.994 ± 0.004
GSE25869 LR NA ± NA NA ± NA NA ± NA NA ± NA
  SVM 0.935 ± 0.024 0.937 ± 0.020 0.938 ± 0.016 0.943 ± 0.014
Breast tissue LR 0.520 ± 0.006 0.961 ± 0.032 0.961 ± 0.044 0.940 ± 0.054
  SVM 0.713 ± 0.108 0.968 ± 0.006 0.970 ± 0.014 0.972 ± 0.010
LSVT LR 0.500 ± 0.000 0.875 ± 0.008 0.846 ± 0.022 0.921 ± 0.012
  SVM 0.500 ± 0.000 0.879 ± 0.012 0.863 ± 0.014 0.919 ± 0.020
DLBCL LR 0.601 ± 0.038 0.608 ± 0.038 0.610 ± 0.048 0.660 ± 0.062
  SVM 0.616 ± 0.050 0.622 ± 0.052 0.619 ± 0.052 0.654 ± 0.054
Myeloma LR 0.500 ± 0.000 0.729 ± 0.044 0.739 ± 0.072 0.746 ± 0.038
  SVM 0.573 ± 0.098 0.748 ± 0.052 0.747 ± 0.054 0.750 ± 0.054
Parkinsons LR 0.875 ± 0.012 0.896 ± 0.054 0.893 ± 0.058 0.906 ± 0.048
  SVM 0.882 ± 0.010 0.875 ± 0.010 0.885 ± 0.024 0.891 ± 0.018
Wdbc LR 0.942 ± 0.002 0.982 ± 0.004 0.978 ± 0.006 0.993 ± 0.004
  SVM 0.990 ± 0.002 0.994 ± 0.002 0.993 ± 0.004 0.995 ± 0.000
Indian Liver LR 0.680 ± 0.002 0.743 ± 0.008 0.742 ± 0.008 0.746 ± 0.010
  SVM 0.636 ± 0.068 0.696 ± 0.008 0.692 ± 0.034 0.695 ± 0.008
Pima Indians Diabetes LR 0.604 ± 0.004 0.827 ± 0.004 0.827 ± 0.004 0.834 ± 0.006
  SVM 0.826 ± 0.004 0.828 ± 0.006 0.828 ± 0.006 0.834 ± 0.006
  1. The performances are measured by the average Area Under the ROC in 5-fold cross-validations. The means and 95 % confidence intervals are included. Column names: None - no data scaling; Minmax - Min-max algorithm; Z-score - Z-score algorithm; GL - GL algorithm. Best performances are emphasized in bold