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Data · dataset · 2025

Interpretation of feature impacts on predicted risk in the CoxBoost model using SHAP

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Description

The impact of features on the predicted risk in the CoxBoost model was interpreted using SHapley Additive exPlanations (SHAP) values. ​​A: Beeswarm plot of global feature importance, showing the distribution of SHAP values for each feature across all samples, where point color represents the feature value. ​​B: Mean absolute SHAP values for global feature importance ranking. ​​C:SHAP waterfall plot for a single sample, illustrating how each feature contributes to pushing the model's base value (average prediction) higher or lower. ​​D~G: SHAP dependence plots illustrating the relationship between the feature value and its impact on the prediction (SHAP value), with D representing Montreal B classification, E showing C-reactive protein (CRP), F indicating fibrinogen (Fg), and G depicting albumin (ALB).

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Inferred from text
Machine learning 68%
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ScienceDB10.57760/sciencedb.3435010 d agoJSON v1
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