Causal Prediction
Introduction
Prerequisites and limitations
Train a causal prediction model
Causal Prediction Settings
Settings: Outcome & Treatment
Settings: Train / Test set
Settings: Metrics
Settings: Algorithms
Settings: Hyperparameters optimization
Settings: Treatment Analysis
Causal Prediction Algorithms
Meta-learning
Causal forest
Causal Prediction Results
Feature importance
Uplift and Qini curves
Distribution of the predicted effect
Treatment Randomization
Positivity Analysis
Scoring recipe
Causal scoring
Propensity scoring
Evaluation recipe
Input dataset
Output datasets