Alternatives and similar repositories for opossum

Users that are interested in opossum are comparing it to the libraries listed below

• Ibotta / mr_uplift
  Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…
  ☆69Updated 3 months ago
• timmens / causal-forest
  Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
  ☆70Updated 5 years ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆51Updated 3 years ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆64Updated last year
• PlaytikaOSS / uplift-analysis
  A Python library that implements scoring utilities, analysis strategies, and visualization methods which can serve uplift modeling use-ca…
  ☆24Updated 2 years ago
• inovex / justcause
  💊 Comparing causality methods in a fair and just way.
  ☆139Updated 5 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆51Updated 4 years ago
• causal-machine-learning / kdd2021-tutorial
  EconML/CausalML KDD 2021 Tutorial
  ☆161Updated last year
• microsoft / SparseSC
  Fit Sparse Synthetic Control Models in Python
  ☆83Updated last year
• andrewtavis / causeinfer
  Machine learning based causal inference/uplift in Python
  ☆61Updated last year
• IBM-HRL-MLHLS / IBM-Causal-Inference-Benchmarking-Framework
  Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code
  ☆84Updated 7 years ago
• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆19Updated last year
• kjung / scikit-learn
  A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.
  ☆22Updated 8 years ago
• industry-bandits / practical-bandits-tutorial
  ☆23Updated 2 years ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 3 years ago
• Minyus / causallift
  CausalLift: Python package for causality-based Uplift Modeling in real-world business
  ☆351Updated 2 years ago
• Nth-iteration-labs / contextual
  Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
  ☆81Updated 5 years ago
• yaronshap / GloballyConsistentRules
  Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…
  ☆25Updated 3 years ago
• bradyneal / causal-book-code
  ☆79Updated 4 years ago
• MLResearchAtOSRAM / cause2e
  The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).
  ☆60Updated 3 months ago
• nlapier2 / PySensemakr
  Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
  ☆52Updated 2 months ago
• matheusfacure / exploratory-notebooks
  Unstructured Code with interesting analysis
  ☆37Updated 9 months ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆116Updated 2 years ago
• duketemon / pyuplift
  Lightweight uplift modeling framework for Python
  ☆28Updated 5 years ago
• MasaAsami / pysynthdid
  Synthetic difference in differences for Python
  ☆83Updated last year
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆143Updated last year
• py-why / causaltune
  AutoML for causal inference.
  ☆227Updated 7 months ago
• AngelPone / pyhts
  A python package for hierarchical forecasting, inspired by hts package in R.
  ☆28Updated 5 months ago
• klostest / uplift_modeling
  ☆17Updated 5 years ago