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Table 14 Classification accuracy, precision, recall, specificity, and F1-score obtained by trained Resnet-101 individual models and by the Resnet101-7 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
Resnet-101-8281 0.8281 0.8376 0.9139 0.6667 0.8741
Resnet-101-8307 0.8307 0.8536 0.8942 0.7114 0.8734
Resnet101-7 ensemble 0.8506 0.8638 0.9155 0.7284 0.8889