Fig. 6 | Scientific Reports

Fig. 6

From: The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms

Fig. 6

Overview of SHAP distribution for each feature in the XGBoost model for PWS. The x-axis represents the SHAP values attributed to each feature, and the y-axis lists the features in descending order of importance. Each point in the plot represents a patient, with the color indicating the feature value in the dataset: red denotes higher values, while blue represents lower values. Positive SHAP values suggest that the feature prompts the model to predict the therapy as effective, while negative SHAP values suggest the feature causes the model to predict the therapy as ineffective.

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