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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.