Fig. 2

Accuracies of the cross-validation and the testing of the models on new, unseen data. a Quality measures for the rule-based models. Averaged Accuracy is the average of mean accuracy from the 10-fold cross-validation loop for the models created on 100 under-sampled subsets for each protein. Standard deviation from the 10-fold cross validation loop, averaged in a similar way as accuracy, is shown as error bars on the plot. b Re-classification of the training sequences of the H5N1 sequences. Accuracy is the percentage of correctly classified sequences. See also Additional file 4: Table S2. c Re-classification of the training sequences of the non-H5N1 sequences. Accuracy is the percentage of correctly classified sequences. See also Additional file 4: Table S3. d Accuracies of the classifiers when tested on the newly published unseen H5N1 sequences, i.e. sequences not included in the training of the models and with sequences identical to the training sequences removed. Accuracy is the percentage of correctly classified sequences. Classifiers consisted of the significant rules from all the rule-based models created for a given protein. See also Additional file 5: Table S4. e Accuracies of the classifiers when tested on the newly published unseen non-H5N1 sequences, i.e. sequences not included in the training of the models and with sequences identical to the training sequences removed. Accuracy is the percentage of correctly classified sequences. Classifiers consisted of the significant rules from all the rule-based models created for a given protein. See also Additional file 5: Table S5