Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals
Fig 6
The distribution of feature impact on model predictions of the treatment (positive SHAP values) and the control group (negative SHAP values) as a SHAP bee-swarm plot.
Every point represents a data instance with clusters indicating the data density. Rows and columns correspond to features and SHAP value, respectively, while color intensity represents the feature value. The red color indicates high values of the considered features, while the blue color represents the opposite case. Features are ranked by their impact on the model output. Data is from a 300-element windows’ experiment on a dataset sampled every 500th instance.