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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning

Fig 3

The AUC values of 32 synthetic-data-trained classifiers (horizontal axis, see Fig 2) on withheld testing sets.

Classifiers are reordered by AUC scores. Error bars correspond to the 95% confidence intervals. DeLong tests are conducted to compare the AUC values of classifiers, with detailed results available in Tables A-D in S2 Text (where the predictive model is fixed) and Tables E-L in S2 Text (where the training data is fixed).

Fig 3

doi: https://doi.org/10.1371/journal.pcbi.1012782.g003