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Fig. 3 | BMC Bioinformatics

Fig. 3

From: The effect of data balancing approaches on the prediction of metabolic syndrome using non-invasive parameters based on random forest

Fig. 3

Feature importance in the MetS prediction model based on different data balancing methods. A Features importance on imbalanced data in men; B features importance on imbalanced data in women; C features importance based on the SMOTE method in men; D features importance based on the SMOTE method in women; E features importance based on the SplitBal method in men; F features importance based on the SplitBal method in women. BMI: body mass index, SBP: systolic blood pressure, DBP: diastolic blood pressure, FH1: family history in a first-degree relative

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BMC Bioinformatics

ISSN: 1471-2105

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