The current version offers:
- H statistics per feature, feature pair, and feature triple
- multivariate predictions at no additional cost
- a convenient API
- other important tools from explainable ML:
- performance calculations
- permutation importance (e.g., to select features for calculating H-statistics)
- partial dependence plots (including grouping, multivariate, multivariable)
- individual conditional expectations (ICE)
- Case-weights are available for all methods, which is important, e.g., in insurance applications.
Click through for an example of how it works, followed by some simple benchmarking to give you an idea of how it performs compared to similar tools.