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Table 18 Average focal loss results (30 runs)

From: Medicare fraud detection using neural networks

Method

\(\alpha\)

\(\gamma\)

Hidden layers

Decision threshold

ROC AUC

TPR

TNR

G-Mean

FL-1-2

0.25

2

2

0.0315

0.8015

0.8741

0.5202

0.6722

FL-1-4

  

4

0.0315

0.8019

0.8167

0.6264

0.7115

FL-2-2

0.25

3

2

0.0730

0.8073

0.7616

0.7019

0.7295

FL-2-4

  

4

0.0730

0.8020

0.7912

0.6595

0.7184

FL-3-2

0.25

4

2

0.1195

0.8071

0.7342

0.7309

0.7310

FL-3-4

  

4

0.1190

0.8025

0.7769

0.6781

0.7230

FL-4-2

0.25

5

2

0.1615

0.8072

0.7574

0.7018

0.7267

FL-4-4

  

4

0.1615

0.8030

0.7646

0.6952

0.7267

  1. Italic font indicates the maximum ROC AUC score