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Table 6 Classification Performance on the Protein-DNA Interaction Site Prediction.

From: svm PRAT: SVM-based Protein Residue Annotation Toolkit

  w= f= 3 w= f= 7 w= f= 11
  ROC F1 ROC F1 ROC F1
0.756 0.463 0.758* 0.469 0.748 0.452
0.753 0.465 0.754 0.462 0.759 0.466
0.754 0.466 0.756 0.468 0.763 0.468
  1. The numbers in bold show the best models for a fixed w parameter, as measured by ROC. , and represent the PSI-BLAST profile and YASSPP scoring matrices, respectively. soe, rbf, and lin represent the three different kernels studied using the as the base kernel. * denotes the best classification results in the sub-tables, and ** denotes the best classification results achieved on this dataset. For the best model we report a Q2 accuracy of 83.0% with an se rate of 0.34.
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