日本語
Predictive AI models are a powerful tool for uncovering subtle predictive relationships between observed variables. But sometimes, you need to draw conclusions about the causal relationship between two variables, not just the observed association. To achieve this "Causal AI", you can use the DataRobot platform and a quasi-experimental technique called "Inverse Propensity of Treatment Weighting". This notebook will apply this technique to data on diabetes hospital patient readmission.
This notebook outlines how to:
Understand Inverse Propensity of Treatment Weighting
Prepare data for a Propensity of Treatment model
Fit a Propensity of Treatment model with DataRobot
Calculate Inverse Propensity of Treatment Weights
Evaluate the causal relationship using Inverse Propensity of Treatment Weighting
