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Table 1 MVCT performance results for all six data sets over 11 iterations of learning. Results demonstrate average area under the precision-recall curves. Standard deviations were in the range of 0.001 to 0.003 for all experiments and are omitted from the table for clarity

From: A semi-supervised machine learning framework for microRNA classification

Iteration hsa exp-based hsa seq-based mmu exp-based mmu seq-based dme exp- based dme seq-based bta exp-based bta seq-based gga exp-based gga seq- based eca exp-based eca seq-based
0.596 0.344 0.714 0.822 0.810 0.864 0.778 0.357 0.925 0.893 0.921 0.875
1 0.681 0.448 0.795 0.881 0.854 0.920 0.866 0.478 0.932 0.909 0.918 0.881
2 0.705 0.568 0.797 0.906 0.884 0.920 0.860 0.566 0.930 0.905 0.926 0.893
3 0.721 0.678 0.813 0.903 0.893 0.920 0.865 0.585 0.927 0.909 0.934 0.886
4 0.752 0.735 0.872 0.912 0.893 0.919 0.850 0.778 0.920 0.912 0.939 0.941
5 0.748 0.734 0.879 0.911 0.886 0.925 0.863 0.726 0.931 0.917 0.952 0.946
6 0.781 0.739 0.921 0.920 0.883 0.912 0.849 0.783 0.923 0.915 0.947 0.947
7 0.771 0.747 0.917 0.910 0.887 0.922 0.871 0.773 0.930 0.911 0.954 0.952
8 0.791 0.744 0.937 0.912 0.882 0.920 0.855 0.734 0.951 0.916 0.943 0.949
9 0.772 0.738 0.928 0.911 0.920 0.932 0.860 0.744 0.957 0.918 0.956 0.955
10 0.773 0.761 0.941 0.908 0.903 0.923 0.865 0.765 0.961 0.917 0.952 0.961
11 0.779 0.761 0.955 0.912 0.901 0.921 0.865 0.809 0.964 0.927 0.959 0.961