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Table 7 Accuracy of the nine trained Resnet-101 individual models in classifying ALL in microscopic images when the best combination of hyperparameters was used in nine independent experimental runs

From: Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method

Model

Accuracy for the training set

Accuracy for the preliminary test set

Resnet-101-8249(#1)

0.9881

0.8249

Resnet-101-8184(#2)

0.9856

0.8184

Resnet-101-8452(#3)

0.9872

0.8452

Resnet-101-8125(#4)

0.9893

0.8125

Resnet-101-8061(#5)

0.9841

0.8061

Resnet-101-8281(#6)

0.9848

0.8281

Resnet-101-8307(#7)

0.9811

0.8307

Resnet-101-8002(#8)

0.9877

0.8002

Resnet-101-8216(#9)

0.9859

0.8216

Average accuracy

0.9860

0.8209

SD

0.0025

0.0136

η value

37.0637

14.9359