Table 4 Performance metrics of the classification model for each organism. The table includes the best cross-validation (CV) accuracy and corresponding test set metrics: accuracy, precision, recall, and F1-score. Higher scores for monocots, insects, and Sauria suggest more distinct or learnable features, while lower scores in other groups indicate potential classification challenges.

From: Comparative analysis of sequential and thermodynamic features of pre-miRNA in insects with various organisms and applying XGBoost for one-vs-rest binary classification

Organism

Best CV Accuracy

Test Accuracy

Test Precision

Test Recall

Test F1

aves

0.68704097

0.658844765

0.650684932

0.685920578

0.667838

human

0.706591391

0.700520833

0.702631579

0.6953125

0.698953

dogs

0.693330745

0.668316832

0.697674419

0.594059406

0.641711

monocots

0.836522619

0.862637363

0.888235294

0.82967033

0.857955

rodent

0.6890823

0.683544304

0.669590643

0.724683544

0.696049

rumin

0.651607728

0.704225352

0.700460829

0.713615023

0.706977

sauria

0.820303403

0.795081967

0.78125

0.819672131

0.8

insect

0.832038193

0.854933726

0.866261398

0.839469809

0.852655

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