Background Given that machine learning is one of the most effective approaches for identifying disease risk factors, this study aimed to explore the predictors of preeclampsia through machine learning...
Machine elements frequently operate under variable conditions, resulting in significant variations in interfacial friction across different lubrication regimes. The Stribeck curve is a well-establishe...
In regression settings, random forests (RFs) often produce unavoidably biased estimates and predictions. We explain sources of bias in terms of RF-based estimated conditional distribution functions (E...
Modeling air quality concentration plays a crucial role in predicting and mitigating airborne pollutant levels. This study collected and organized daily average air quality data and meteorological dat...
The El Niño-Southern Oscillation (ENSO) is a major driver of climate and agricultural productivity variability, as those events modulate significant fraction of rainfall and air temperature interannua...
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