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.
Before, when creating a linear regressor with fixed parameters, the parameters would be overridden upon fitting to data. Now, the parameters remain fixed.
Before, when creating a linear regressor with fixed parameters, the parameters would be overridden upon fitting to data. Now, the parameters remain fixed.