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Table 12 Classification accuracy, precision, recall, specificity, and F1-score obtained by trained Resnet-101 individual models and by the Resnet101-5 ensemble model for the preliminary test set

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

Model

Accuracy

Precision

Recall

Specificity

F1-score

Resnet-101-8249

0.8249

0.8436

0.8983

0.6867

0.8701

Resnet-101-8184

0.8184

0.8624

0.8589

0.7423

0.8607

Resnet-101-8452

0.8452

0.8582

0.9139

0.716

0.8852

Resnet-101-8125

0.8125

0.8376

0.8843

0.6775

0.8603

Resnet-101-8061

0.8061

0.8562

0.845

0.733

0.8505

Resnet101-5 ensemble

0.8436

0.8641

0.9024

0.733

0.8828

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BMC Bioinformatics

ISSN: 1471-2105

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