CausalNex
CausalNex, an open source Python library, allows us to develop models that help to infer causation rather than observing correlation. The what if
library offered by CausalNex is deployed to test scenarios utilizing Bayesian networks and develop causal reasoning. Some prominent features of CausalNex are as follows:
- Simplifying causality understanding in Bayesian networks via visualization: One of the main features of CausalNex is its ability to simplify the understanding of causality in Bayesian networks through visualizations. The library provides a range of tools for visualizing Bayesian networks, including network plots, influence plots, and decision plots, which allow users to see how different variables are connected and how they influence each other.
- Understanding conditional dependencies between variables: CausalNex also provides tools for understanding conditional dependencies between variables. The library includes state-of-the-art structure learning methods...