Netflix / sherlock
R package for causal machine learning for segment discovery and analysis
☆31Updated last year
Alternatives and similar repositories for sherlock:
Users that are interested in sherlock are comparing it to the libraries listed below
- 🎯 Targeted Learning in R: A Causal Data Science Handbook☆59Updated 3 months ago
- 📦 Your One Stop to Targeted Learning in R with the tlverse☆33Updated 3 years ago
- eXtreme RuleFit (sparse linear models on XGBoost ensembles)☆43Updated 2 years ago
- R package to send requests to Microsoft Teams through Webhooks☆49Updated 9 months ago
- tidymodels code for the book Applied Predictive Modeling☆43Updated 2 years ago
- ☆49Updated 2 years ago
- The goal of fastDummies is to quickly create dummy variables (columns) and dummy rows.☆36Updated last week
- Example datasets for tsibble☆25Updated 2 months ago
- Tutorials on Stan for Bayesian causal inference☆19Updated last year
- Analysis of simulation studies including Monte Carlo error☆28Updated 8 months ago
- Documents to plan and discuss future development☆37Updated 4 months ago
- tidymodels code for Applied Predictive Modeling☆37Updated 3 years ago
- Parsnip backends for `tree`, `lightGBM` and `Catboost`☆86Updated 2 years ago
- causact: R package to accelerate computational Bayesian inference workflows in R through interactive visualization of models and their o…☆45Updated last week
- Fast Naive Bayes implementation in R☆42Updated 4 years ago
- Machine learning explanations☆22Updated 6 months ago
- ☆20Updated 6 years ago
- Effects and Importances of Model Ingredients☆37Updated last year
- Structure mining for xgboost model☆26Updated 3 years ago
- ☆17Updated last year
- Example workflows for the drake R package☆56Updated 3 years ago
- Bayesian Inference of Complex Panel Data☆29Updated 2 months ago
- Friedman's H-statistics☆29Updated this week
- Taking Uncertainty Seriously: Bayesian Marginal Structural Models for Causal Inference in Political Science☆18Updated 2 years ago
- useR! 2019 Tutorial: Automatic and Explainable Machine Learning with H2O in R (http://www.user2019.fr/tutorials/)☆26Updated 5 years ago
- R Bindings to the Certifiably Optimal Rule Lists (Corels) Learner☆47Updated last month
- miceRanger: Fast Imputation with Random Forests in R☆67Updated 2 years ago
- An R package for conducting sensitivity analyses for unmeasured confounders☆34Updated 11 months ago
- mlr3 extension for Fairness in Machine Learning☆14Updated 5 months ago
- 🎯🎓 Generalized Targeted Learning Framework☆37Updated 2 months ago