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Table 2 Generalization performance scores of the LSTM-FC model

From: A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks

Metrics

Testing

Generalization Evaluation

Fold 4

Fold 5*

Fold 6

Fold 7

Fold 8

Presion

0.68319

0.580241

0.659877

0.612346

0.593226

0.602658

Recall

0.92841

0. 978,764

0.993714

0.975116

0.948571

0.984286

Accuracy

0.65295

0.580241

0.642169

0.606024

0.580000

0.598072

F1-Score

0.77592

0.738147

0.798413

0.769355

0.752720

0.769421

  1. Note: Fold 5 is highlighted (*) as the best-performing fold due to its superior Precision, Recall, Accuracy, and F1-Score compared to other folds. The Testing column represents the evaluation of the model's performance on an unseen test dataset
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ISSN: 1756-0381