❗ uplift modeling in scikit-learn style in python 🐍
-
Updated
Oct 21, 2023 - Python
❗ uplift modeling in scikit-learn style in python 🐍
pytorch implementation of dragonnet
A Python Framework for Automatically Evaluating various Uplift Modeling Algorithms to Estimate Individual Treatment Effects
Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
The package is developed for treatment recommendation & pairwise treatment individual effect estimation (ITE/CATE/HTE) when multiple treatment/intervention options exist. The package is still under development.
Repository of the algorithm Propensity Score Synthetic Augmentation Matching using Generative Adversarial Networks (PSSAM-GAN)
Evaluating BART and Synthetic Tree-Based Methods for the Estimation of Individual Causal Effects, final project for CM764 - Statistical Learning - Function Estimation at uWaterloo
Code library for training causal inference deep learning models with automatic hyperparameter optimization written in Tensorflow 2.
Code and Datasets for the paper "Estimating Individual Treatment Effects with Time-Varying Confounders", published on ICDM 2020.
Official repository of DR-VIDAL - accepted in AMIA' 22 (Oral)
Add a description, image, and links to the individual-treatment-effects topic page so that developers can more easily learn about it.
To associate your repository with the individual-treatment-effects topic, visit your repo's landing page and select "manage topics."