Measuring the completeness of a data population often requires either expert knowledge or the presence of reference data. If neither is available, measuring population completeness becomes nontrivial. We present the ForCE approach (Forecasting for Completeness Estimation), a method to estimate the completeness of timestamped data using time series forecasting. We evaluate the method’s feasibility using a medical domain real-world dataset, which we provide for download. The method is compared to three baselines. ForCE manages to surpass all three.
CITATION STYLE
Endler, G., Baumgärtel, P., Wahl, A. M., & Lenz, R. (2015). ForCE: Is estimation of data completeness through time series forecasts feasible. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9282, pp. 261–274). Springer Verlag. https://doi.org/10.1007/978-3-319-23135-8_18
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