Using Active Learning for Speeding up Calibration in Simulation Models

Conclusion. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration.

Source: Medical Decision Making - May 24, 2016 Category: Health Management Authors: Cevik, M., Ergun, M. A., Stout, N. K., Trentham-Dietz, A., Craven, M., Alagoz, O. Tags: Original Articles Source Type: research