Alternatives and similar repositories for APA

Users that are interested in APA 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…
  ☆70Updated 5 months ago
• rsyi / pylift
  Uplift modeling and evaluation library. Actively maintained pypi version.
  ☆77Updated last year
• duketemon / pyuplift
  Lightweight uplift modeling framework for Python
  ☆28Updated 5 years ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆52Updated 4 years ago
• causal-machine-learning / kdd2021-tutorial
  EconML/CausalML KDD 2021 Tutorial
  ☆163Updated 2 years ago
• jeremite / channel-attribution-model
  An attention-based Recurrent Neural Net multi-touch attribution model in a supervised learning fashion of predicting if a series of event…
  ☆34Updated 4 years ago
• Minyus / causallift
  CausalLift: Python package for causality-based Uplift Modeling in real-world business
  ☆349Updated 2 years ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆67Updated last year
• ianchute / shapley-attribution-model-zhao-naive
  A Python implementation of "Shapley Value Methods for Attribution Modeling in Online Advertising" by Zhao, et al.
  ☆41Updated 5 years ago
• eeghor / mta
  Multi-Touch Attribution
  ☆117Updated 3 years ago
• bookingcom / upliftml
  UpliftML: A Python Package for Scalable Uplift Modeling
  ☆327Updated 2 years ago
• DallasBuyer / awesome-dynamic-pricing
  😎 awesome dynamic pricing 💵
  ☆112Updated 2 years ago
• psarka / uplift
  ☆34Updated 7 years ago
• DiegoUsaiUK / Propensity_Modelling
  Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign
  ☆27Updated 2 years ago
• timmens / causal-forest
  Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
  ☆69Updated 5 years ago
• ing-bank / skorecard
  scikit-learn compatible tools for building credit risk acceptance models
  ☆103Updated 7 months ago
• benmiroglio / pymatch
  ☆289Updated 2 years ago
• rk2900 / deep-conv-attr
  An implementation of our CIKM 2018 paper "Deep Conversion Attribution with Dual-attention Recurrent Neural Network"
  ☆61Updated 6 years ago
• google / lifetime_value
  ☆362Updated last year
• wayfair / pylift
  Uplift modeling package.
  ☆375Updated 2 years ago
• konosp / propensity-score-matching
  ☆104Updated 4 years ago
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆58Updated 3 years ago
• OscarEngelbrektson / SyntheticControlMethods
  A Python package for causal inference using Synthetic Controls
  ☆191Updated last year
• copperheadCrotch / Sequential-Probability-Ratio-Test
  Python package for Wald's sequential probability ratio test
  ☆47Updated 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
• PGuti / Uplift
  About uplift modeling
  ☆30Updated 8 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).
  ☆63Updated 5 months ago
• microsoft / SparseSC
  Fit Sparse Synthetic Control Models in Python
  ☆87Updated last year
• jgitr / opossum
  ☆17Updated 6 years ago
• smazzanti / tds_black_box_models_more_explainable
  Jupyter Notebook used for writing the article "Black-Box models are actually more explainable than a Logistic Regression" published in To…
  ☆73Updated 2 years ago