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Table 1 Mean of imputation accuracy for Boosting methods in various versions on the four different datasets

From: Comparison of three boosting methods in parent-offspring trios for genotype imputation using simulation study

Data set Density Sample size Version AB LB TB
  5 k 100 NA10 0.9843 0.9954 0.9611
  5 k 100 NA30 0.9883 0.9947 0.9638
G1 5 k 100 NA50 0.9822 0.9909 0.9621
  5 k 100 NA70 0.9777 0.9829 0.9583
  5 k 100 NA90 0.9211 0.9303 0.9246
    Mean 0.9707 0.9788 0.9539
  10 k 100 NA10 0.9861 0.9981 0.9702
  10 k 100 NA30 0.9886 0.9978 0.9697
G2 10 k 100 NA50 0.9912 0.9970 0.9679
  10 k 100 NA70 0.9898 0.9939 0.9647
  10 k 100 NA90 0.9653 0.9714 0.9523
    Mean 0.9842 0.9916 0.9649
  5 k 500 NA10 0.9859 0.9967 0.9650
  5 k 500 NA30 0.9885 0.9952 0.9650
G3 5 k 500 NA50 0.9877 0.9926 0.9638
  5 k 500 NA70 0.9800 0.9848 0.9618
  5 k 500 NA90 0.9288 0.9383 0.9362
    Mean 0.9741 0.9815 0.9583
  10 k 500 NA10 0.9787 0.9983 0.9706
  10 k 500 NA30 0.9799 0.9977 0.9692
G4 10 k 500 NA50 0.9830 0.9967 0.9665
  10 k 500 NA70 0.9877 0.9959 0.9634
  10 k 500 NA90 0.9706 0.9767 0.9552
    Mean 0.9799 0.9930 0.9649
  1. NA10: 10 % of genotype is missing per offspring, NA30: 30 % of genotype is missing per offspring, NA50: 50 % of genotype is missing per offspring, NA70: 70 % of genotype is missing per offspring, NA90: 90 % of genotype is missing per offspring, Bold: Mean of different versions in each dataset
  2. AB AdaBoost, LB LogitBoost, TB TotalBoost