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Table 3 The performance of correctness with the best pair of (dcn,kvar) for each threshold of the size of the model among training dataset. The best pairs are chosen from the result in Fig. 2 that shows best microAUC score in the same thresholds. We note that 10-fold cross validation is used on the training set

From: Secure tumor classification by shallow neural network using homomorphic encryption

Threshold of the model size

dcn

kvar

Filtered genes

microAUC

Accuracy

   

CN

Variants

  

512

0.17

60

243

265

0.98179

0.83321

1024

0.13

90

358

404

0.98523

0.84317

2048

0.08

270

709

1198

0.98625

0.86827

4096

0.08

550

709

2364

0.98704

0.86974