There are now many papers in economics that discuss counterfactual prediction. How can machine learning be combined with the field of economics to help counterfactual prediction?
Dear Shenghao Bi ,
In interpretable machine learning, counterfactual explanations can be used to explain predictions of individual instances. The “event” is the predicted outcome of an instance, the “causes” are the particular feature values of this instance that were input to the model and “caused” a certain prediction.
https://christophm.github.io/interpretable-ml-book/counterfactual.html
Regards,
Shafagat
1) Define the Treatment
2) Collect Data
3) Preprocess Data
4) Define the Causal Model
5) Train a Counterfactual Predictor
6) Evaluate the Predictor
7) Generate Counterfactual Predictions
8) Interpret and Validate Results
- Badges
- Science topic
- Similar topics
- Engineering
- Control Theory
- Control Systems
- Control Systems Engineering