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Search results for python treatment effects
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9 search results found
Dowhy
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6,730
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Catenets
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90
Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
Causeinfer
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54
Machine learning based causal inference/uplift in Python
Network Deconfounder Wsdm20
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35
Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
Causalegm
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35
A General Causal Inference Framework by Encoding Generative Modeling
Openasce
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35
OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one package.
Pyuplift
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19
Python uplift modeling implementation
Cfml_tools
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12
My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context
Cikm18 Lcva
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12
Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
Bites
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11
BITES: Balanced Individual Treatment Effect for Survival data
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