crflynn / skranger
scikit-learn compatible Python bindings for ranger C++ random forest library
☆52Updated last year
Alternatives and similar repositories for skranger:
Users that are interested in skranger are comparing it to the libraries listed below
- Compute SHAP values for your tree-based models using the TreeSHAP algorithm☆84Updated 9 months ago
- An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model☆75Updated 4 years ago
- Hierarchical and Grouped Time Series☆111Updated 4 months ago
- Trees are all you need☆114Updated 11 months ago
- Adaptive and automatic gradient boosting computations.☆68Updated 2 years ago
- Distributional Random Forests (Cevid et al., 2020)☆43Updated last year
- Nested cross-validation for accurate confidence intervals for prediction error.☆41Updated 2 years ago
- mixgb: multiple imputation through XGBoost☆23Updated 3 weeks ago
- Surrogate Assisted Feature Extraction☆37Updated 3 years ago
- Version, share, deploy, and monitor models.☆66Updated last month
- code and demo for hierarchical stacking paper☆10Updated 3 years ago
- Parallelizable Bayesian Optimization in R☆109Updated 2 years ago
- miceRanger: Fast Imputation with Random Forests in R☆68Updated 2 years ago
- Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)☆84Updated last year
- Explaining the output of machine learning models with more accurately estimated Shapley values☆158Updated this week
- A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …☆63Updated 3 years ago
- Adversarial Random Forests☆15Updated last month
- A C++ library for vine copula models (w/ interfaces to R + Python)☆35Updated last week
- A Python package with explanation methods for extraction of feature interactions from predictive models☆30Updated last year
- Tool for exploring probability distributions.☆23Updated 4 months ago
- eXtreme RuleFit (sparse linear models on XGBoost ensembles)☆43Updated 2 years ago
- Single- and Multi-Objective Optimization Test Functions☆36Updated last year
- Rlgt is an R package for Bayesian Exponential Smoothing☆20Updated 2 weeks ago
- An R package to assess feature importance☆33Updated 3 years ago
- Fast approximate Shapley values in R☆121Updated last year
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- An R package with Python support for multi-step-ahead forecasting with machine learning and deep learning algorithms☆130Updated 4 years ago
- autoxgboost - Automatic tuning and fitting of xgboost☆123Updated 3 years ago
- ☆110Updated last week
- Fast implementation of Venn-ABERS probabilistic predictors☆72Updated last year