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Table 1 Hierarchical SVM classifier performance on training dataset for Level 1 predictions.

From: Cost sensitive hierarchical document classification to triage PubMed abstracts for manual curation

Level 1 category Curatable abstracts AUC individual category (SVM) Category prediction accuracy (%)(MLP)
Allergy 1146 0.994 91.6
Autoimmunity 4350 0.988 88.9
Infectious Disease 7525 0.989 92.7
Transplantation 888 0.985 76.4
HIV 2369 0.989 92.6
Cancer 2650 0.988 89.8
Other 3905 0.985 85.4
Total 22833   89.7
  1. Performance was evaluated with 10-fold cross-validation. An AUC value was calculated for a given category, where documents assigned by the expert to be of that category are considered "positive" while documents assigned to any other category are negative. To evaluate the performance of the document classification by the Multilayer Perceptron (MLP) into specific categories, we calculated the percent agreement of categories. The AUC and category prediction accuracy values are entered for each Level 1 category in addition to the total prediction accuracy.