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Table 3 Comparison of prediction performance

From: Cutoff Scanning Matrix (CSM): structural classification and function prediction by protein inter-residue distance patterns

Dataset SCOP level CSM+SVD Jain et al. ∆Prec. ∆Rec.
   Prec . Recall F1 Prec . Recall F1   
3SSE Class 0.991 0.991 0.991 0.890 0.840 0.864 +10.1% +15.1%
  Fold 0.956 0.957 0.956 0.860 0.450 0.591 +9.6% +50.7%
  Superfamily 0.956 0.957 0.956 0.800 0.550 0.652 +15.6% +40.7%
  Family 0.935 0.935 0.935 0.820 0.870 0.844 +11.5% +6.5%
4SSE Class 0.961 0.962 0.961 0.990 0.990 0.990 -2.9% -2.8%
  Fold 0.939 0.939 0.938 0.960 0.830 0.890 -2.1% +10.9%
  Superfamily 0.938 0.937 0.937 0.880 0.690 0.774 +5.8% +24.7%
  Family 0.935 0.934 0.933 0.980 0.920 0.949 -4.5% +1.4%
5SSE Class 0.985 0.985 0.985 0.980 1.000 0.990 +0.5% -1.5%
  Fold 0.969 0.969 0.969 1.000 0.690 0.817 -3.1% +27.9%
  Superfamily 0.970 0.969 0.969 0.980 0.650 0.782 -1.0% +31.9%
  Family 0.967 0.965 0.965 0.980 0.920 0.949 -1.3% +4.5%
6SSE Class 0.966 0.965 0.965 0.970 1.000 0.985 -0.4% -3.5%
  Fold 0.943 0.943 0.942 0.950 0.510 0.664 -0.7% +43.3%
  Superfamily 0.937 0.939 0.937 0.950 0.570 0.713 -1.3% +36.9%
  Family 0.932 0.932 0.930 0.980 0.840 0.905 -4.8% +9.2%
  1. A comparison of prediction performance between the current study and the method introduced by [29]. The precision and recall metrics are weighted averages. This result comprises a 10-fold cross validation in KNN.