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Table 8 Comparative results for the remote homology detection problem on dataset sf95.

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

  Ie et al [19]   Scaling Model   Best Model  
  ZE BE ZE BE ZE BE
Without Hierarchy Information
Ranking Perceptron 21.8 36.7 9.3 16.1 9.3 16.1
SVM-Struct 20.7 37.6 9.0 15.9 9.0 15.9
With Fold-level Nodes
SVM-Struct 20.4 37.5 11.2 19.6 10.1 19.3
  1. The results for Ie et al were obtained from the supplementary website for the work [19], and represent the results obtained using the simple scaling model in their implementation. The results labeled "Scaling Model" correspond to the performance achieved by our two-level classifiers using the simple scaling model, whereas the results labeled "Best Model" correspond to the best performance achieved among the simple scaling, scaling & shift, and Cramer-Singer models. Both of these results were obtained from Table 2. All results were obtained by optimizing the balanced loss function. ZE and BE denote the zero-one error and balanced error percent rates respectively.