Skip to main content

Table 5 Zero-one and Balanced error rates for the fold recognition problem optimized for the zero-one loss function.

From: Building multiclass classifiers for remote homology detection and fold recognition

   fd25 fd40
   ZE BE ZE BE
MaxClassifier   42.0 60.3 44.4 64.6
Direct K-way Classifiers   42.8 59.4 43.0 62.7
Two-Level Approaches Without Hierarchy Information
  Scaling 39.9 52.9 32.2 50.6
Ranking Perceptron Scale & Shift 38.4 51.3 27.3 44.8
  Crammer Singer 34.8 48.9 37.7 56.6
  Scaling 41.3 55.2 33.7 50.0
SVM-Struct Scale & Shift 41.0 54.3 29.0 46.2
  Crammer Singer 36.6 49.4 32.5 49.6
Two-Level Approaches With Class-level Nodes
  Scaling 39.9 52.2 31.9 50.2
SVM-Struct Scale & Shift 38.4 52.9 29.3 44.6
  Crammer Singer 39.2 51.8 32.8 52.9
Two-Level Approaches With Superfamily-level Nodes
  Scaling 39.5 53.9 31.3 48.8
SVM-Struct Scale & Shift 39.9 53.4 31.3 48.4
  Crammer Singer 37.7 52.1 33.4 51.0
Two-Level Approaches With Superfamily-level and Class-level Nodes
  Scaling 39.2 52.2 27.3 41.0
SVM-Struct Scale & Shift 39.9 53.9 28.4 44.1
  Crammer Singer 38.8 54.7 31.3 48.0
  1. ZE and BE denote the zero-one error and balanced error percent rates respectively. The results were obtained by optimizing the zero-one loss function.