DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
When calling fit inside refutation methods, the effect_modifier_names was passed without name. Now it is a named parameter and avoids getting mixed up with other parameters.
Also generalized econml_fit_params to fit_params since other methods can also have fit_params.
Fixes #1028
When calling
fitinside refutation methods, theeffect_modifier_nameswas passed without name. Now it is a named parameter and avoids getting mixed up with other parameters. Also generalizedeconml_fit_paramstofit_paramssince other methods can also havefit_params.