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Data were preprocessed using R (The R Project), and the models were executed using XGBoost [23] and Sci-Kit Learn (David Cournapeau) [24] backends in Python (version 3.8; Python Software Foundation).
The model’s hyperparameters were selected using a sparse grid search, exploring a reasonable number of hyperparameter combinations while excluding combinations that would obviously underperform or not substantially enhance performance.
JMIR Form Res 2023;7:e45979
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