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Table 9 Mean AUPRC values by classifier and number of features (Part 2) for ten iterations of five-fold cross validation, for part D scenario two

From: Data reduction techniques for highly imbalanced medicare Big Data

Features classifier

15

20

25

30

82

CatBoost

0.8016

0.7953

0.7962

0.7949

0.7797

ET

0.4954

0.4647

0.4605

0.4391

0.3275

LightGBM

0.4447

0.4661

0.4603

0.4841

0.4982

Logistic regression

0.3669

0.3536

0.3519

0.2939

0.3047

Random forest

0.6097

0.5398

0.5519

0.5249

0.2429

XGBoost

0.7889

0.7448

0.7589

0.7548

0.7376

  1. The bold values indicates the maximum value for the classifier