Length of stay prediction model of indoor patients based on light gradient boosting machine

HIGHLIGHTS

  • who: Xiangrui Zeng from the School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia have published the Article: Length of Stay Prediction Model of Indoor Patients Based on Light Gradient Boosting Machine, in the Journal: Computational Intelligence and Neuroscience 11 of 30/08/2022
  • what: In the study, five ML algorithms (LR, RR, RFR, XGBR, and LightGBM) and six feature encoding methods (label encoding, count encoding, one-hot encoding, target encoding, leave-one-out encoding, and the proposed encoding method) were used and compared during the model building. The "Length of Stay" in the dataset . . .

     

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