Figure 5

AUC for different choices of ν and increasing numberof iterations. Change in AUC for different choices of ν (left). The Baum-Welch model performs better for relatively small values of ν while Viterbi training favours larger ν. Improvements in AUC with increasing number of iterations (right). The performance of the Viterbi trained model improves substantially during the first five iterations. Further iterations only produce small changes in the AUC. The Baum-Welch method requires more iterations to obtain the same AUC as as the Viterbi model. After 20 iterations the Baum-Welch model starts to outperform the Viterbi model.