Welcome to YLearn’s documentation!

YLearn, a pun of “learn why”, is a python package for causal learning which supports various aspects of causal inference ranging from causal effect identification, estimation, and causal graph discovery, etc.

• User Guide
  • Overview of YLearn and Causal Inference
  • Quick Start
  • API: Interacting with YLearn
• Causal Model: The Representation of Causal Structures
  • Causal Graph
  • Causal Model
  • Representation of Probability
• Estimator Model: Estimating the Causal Effects
  • Problem Setting
  • Estimator Models
• Causal Discovery: Exploring the Causal Structures in Data
  • No-Tears
• Policy: Selecting the Best Option
  • Class Structures
• Interpreter: Explaining the Causal Effects
  • CEInterpreter
  • PolicyInterpreter
• Why: An All-in-One Causal Learning API
  • Example usages
  • Class Structures
• References

Indices and tables

• Index

• Module Index

• Search Page