Quantco / metalearners
MetaLearners for CATE estimation
☆39Updated 2 weeks ago
Alternatives and similar repositories for metalearners:
Users that are interested in metalearners are comparing it to the libraries listed below
- Rethinking machine learning pipelines☆28Updated 5 months ago
- Decorators for logging purposes for all your dataframes☆11Updated 2 months ago
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆51Updated 4 months ago
- MLflow logging for PyMC☆8Updated 3 weeks ago
- ☆66Updated 2 weeks ago
- This is the repository for the Python library mlsynth☆24Updated last week
- Tools for diagnostics and assessment of (machine learning) models☆34Updated last month
- Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)☆13Updated 7 months ago
- Formulas for mixed-effects models in Python☆58Updated 2 months ago
- Bayesian Conjugate Models in Python☆25Updated this week
- Distributional Random Forests (Cevid et al., 2020)☆43Updated last year
- Prune your sklearn models☆19Updated 5 months ago
- Efficient matrix representations for working with tabular data☆120Updated last week
- Toolkit to forge scikit-learn compatible estimators☆18Updated 3 weeks ago
- WarpGBM: High-Speed Gradient Boosting☆49Updated this week
- 🥄✨Time-series Benchmark methods that are Simple and Probabilistic☆41Updated last year
- A system for Bayesian estimation of state space models using PyMC☆33Updated last year
- Exploratory repository to study predictive survival analysis models☆34Updated last year
- ☆10Updated 5 months ago
- A Python package with explanation methods for extraction of feature interactions from predictive models☆30Updated last year
- ☆107Updated last week
- That's weird: Anomaly detection using R☆42Updated 4 months ago
- Gradient Boosting Modules for pytorch☆22Updated last week
- Competing Risks and Survival Analysis☆95Updated last week
- An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".☆24Updated 10 months ago
- Python package implementing transformers for pre processing steps for machine learning.☆58Updated last week
- High performance Python GLMs with all the features!☆328Updated 2 weeks ago
- R package to compute distribution-free prediction bands using density estimators☆9Updated 3 years ago
- A multiverse of Prophet models for timeseries☆47Updated last week