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. 2022 Sep 29;22(19):7409. doi: 10.3390/s22197409
Algorithm 3 The algorithm for the BoostedEnsML
  • 1:

    Define the number of folds in the split, s

  • 2:

    Initialize s = 0

  • 3:

    while s ⩽ 10 do:

  • 4:

         Train the selected classifier (LGBM or XGB) using 9 parts of the 10 folds and perform prediction on the other part

  • 5:

         XGB and LGBM are used for predictions on the train set and test data.

  • 6:

         s += 1

  • 7:

    end while

  • 8:

    Using Stacking Classifier to combine the predictions from the two base models.

  • 9:

    BoostedEnsML is applied to the test data to make final predictions.