Table 3 Evaluation of the suggested feature selection technique (bGGO) in comparison to other competitive techniques.

From: Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory

 

bGGO

bBER

bDTO

BPSO

bWAO

bGWO

bFAO

Average error

0.286625

0.303825

0.317425

0.337625

0.337425

0.323925

0.336025

Average select size

0.239425

0.439425

0.381825

0.439425

0.602825

0.362225

0.473925

Average fitness

0.349825

0.366025

0.377425

0.364425

0.372225

0.372125

0.416325

Best fitness

0.251625

0.286325

0.280725

0.344725

0.336325

0.349925

0.335025

Worst fitness

0.350125

0.353225

0.395825

0.412425

0.412425

0.426125

0.432625

Standard deviation fitness

0.172125

0.176825

0.178425

0.176225

0.178425

0.177425

0.213025

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