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Table 4 Evaluation of all the methods by cross validation on New York dataset at genus level

From: Prediction of microbial communities for urban metagenomics using neural network approach

Evaluation metric

Methods

Precision

Recall

F1 score

Ranking loss

IDW

0.5669

0.6686

0.6129

0.1790

kNN

0.7203

0.5109

0.5977

0.1273

SVM

0.7510

0.4787

0.5845

0.0725

Random Forest (RF)

0.7288

0.5026

0.5941

0.1365

Neural Network

0.7419

0.5110

0.6050

0.0718

MetaMLAnn

0.7456

0.5325

0.6212

0.0682

MetaMLAnn+ IDW

0.6578

0.6170

0.6363

0.0688

  1. Higher precision, recall, F1 score, and lower ranking loss indicate better performance. Bold entries indicate best performance among different methods
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Human Genomics

ISSN: 1479-7364