A TSC framework separates historical attendance sequences from future labels and uses LSTM-FCN with BFL or G-Mean loss to achieve approximately 80% balanced accuracy for proactive absenteeism prediction on simulated data.
Classification model for reducing absenteeism of nurses at hos- pitals using machine learning and artificial neural network techniques
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A time-series classification framework for individual-level absenteeism prediction under severe class imbalance
A TSC framework separates historical attendance sequences from future labels and uses LSTM-FCN with BFL or G-Mean loss to achieve approximately 80% balanced accuracy for proactive absenteeism prediction on simulated data.