SHAP Plots for 'XGBoost'
Bins a variable into n_bins quantile groups.
Modify labels for features under plotting
Internal-function to revise axis label for each feature
Make customized scatter plot with diagonal line and R2 printed.
Simple scatter plot, adding marginal histogram by default.
Variable importance as measured by mean absolute SHAP value.
SHAP dependence plot and interaction plot, optional to be colored by a...
Make the SHAP force plot
Make the stack plot, optional to zoom in at certain x or certain clust...
SHAP summary plot core function using the long format SHAP values
A wrapped function to make summary plot from model object and predicto...
A wrapped function to make summary plot from given SHAP values matrix
Prepare the interaction SHAP values from predict.xgb.Booster
Prepare SHAP values into long format for plotting
Prepare data for SHAP force plot (stack plot)
Get SHAP scores from a trained XGBoost or LightGBM model
Finds variable with presumably strongest interaction effect.
Aid in visual data investigations using SHAP (SHapley Additive exPlanation) visualization plots for 'XGBoost' and 'LightGBM'. It provides summary plot, dependence plot, interaction plot, and force plot and relies on the SHAP implementation provided by 'XGBoost' and 'LightGBM'. Please refer to 'slundberg/shap' for the original implementation of SHAP in 'Python'.
Useful links