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Table 8 Mean AUPRC values by classifier and number of features (Part 1) 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

7a

7b

8

9

10

CatBoost

0.7575

0.7582

0.7570

0.7558

0.7585

ET

0.5941

0.5171

0.5585

0.6006

0.5878

LightGBM

0.4548

0.4533

0.4689

0.5116

0.5529

Logistic Regression

0.3468

0.3368

0.3497

0.3482

0.3537

Random Forest

0.5873

0.4937

0.5927

0.5393

0.5903

XGBoost

0.7533

0.7539

0.7533

0.7514

0.7571

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